The Hypothetico-Deductive Method
Science is not simply "a body of knowledge". Rather, it is the systematic acquisition and application of knowledge about the structure and behavior of the physical universe gained via empirical evidence through observation, measurement, and experimentation. It can be described as a type of inquiry into nature characterized by the availability of empirically testable hypotheses.

Science starts from several important observations about the world around us:

• Humans are limited by our senses: we cannot have total knowledge of the Universe or any part of it
• The world is sensible: it operates under patterns of operation which we can discover, at least partially
• Although we might never totally understand a given phenomenon, we can approximate or model how it works. Using various types of observations, estimates, and so forth, we can make successive approximations which get progressively "better" (that is, closer to the actual answer)

Science is thus a self-correcting mechanism: it contains within its operation the means to get rid of old, less-accurate models and replace them with more accurate ones.

Argument: a connected series of statements intended to establish a proposition, consisting of one or more premises which support the conclusion. (In the case of Science, the premises should be a series of hypotheses tested against observations.) Many, many fields fields of intellectual endeavor (politics, philosophy, marketing, etc.) relay on arguments. However, Science is distinguished (in a subset of fields: we can add some others like history, economics, etc. in here) by relying on not merely argument butindependent evidence: in other words, it is empirical.

There is much talk about the "Scientific Method", often characterized as a hierarchy of observations --> hypotheses --> theories --> laws. This is in some ways an oversimplification, and in others misses the point. These are more the products of Science, not their method. Perhaps a better descriptor of the "Scientific Method" is simply: Physical Evidence and Reasoned Logic (PEARL).

That physical evidence goes by several names: observations, data, measurements, all meaning the same thing: qualitative or (more commonly) quantitative attribute of a phenomenon. In principle, different observes should be able to make the same measurements/descriptions and find the same value.

Of course, we face the issue of uncertainty: there are limitations of observations (for example, the accuracy and resolution of instruments) so we will not always find the same exact value. Additionally, there are probabilistic aspects to the nature of the Universe, especially at the quantum level.

Raw observations are good, but we need to do more with them. In other words, there must be some form of data analysis. The observations are compared to each other in some fashion (normally some form of mathematical or statistical plot) in order to discover potential patterns, and from that to test different hypotheses.

Collectively, raw observations and analytical results are what we call evidence. We use this evidence to infer what is happening; that is, evidence is used to get to conclusions.

After observing some phenomenon, a pattern often emerges. We can state this pattern formally as an hypothesis. Thus, contrary to its colloquial use, an hypothesis is NOT an "educated guess", but rather "a formal statement of a pattern that appears to exist in a set of observations." In contrast to theories, hypotheses are primarily about the pattern itself, not about an explanation of the pattern.

Unfortunately, humans cannot help but see patterns: castles in the clouds, faces in random objects, "lucky streaks" in games, etc. Not all perceived patterns are real! So to evaluate whether a pattern that we perceive (an hypothesis) might be true, we must test it. We refer to this as "submitting it to falsification": subjecting the hypothesis to some evaluation where it could in principle be shown to be incorrect. Not all hypotheses are falsifiable (synonym: testable): some are purely subjective (e.g., "chocolate is better than vanilla") or involve metaphysical qualities or entities which cannot be measured (e.g., "true justice is superior to true wisdom"). We might hold these as important concepts, but they are outside Science. Indeed, to paraphrase the late philosopher Christopher Hitchens, "What can be asserted without evidence can be dismissed without evidence".

Other hypotheses can be potentially falsifiable with total knowledge of the universe, but we are currently [and perhaps forever] incapable of evaluating (e.g., "the flesh of eurypterids ('water scorpions', extinct for 252 million years) is an effective cure for athletes foot"). Ideas of this second sort are speculations: nothing wrong with them as such, but they aren't particularly useful.

Even good scientific hypotheses remain mere speculations until submitted to a test (often called an experiment). An experiment (i.e., a test of falsification) must be constructed in such a way that the hypothesis could yield observations that demonstrate that the hypothesis is false. For example, we can speculate that "my horse can outrun any horse in the world." However, until we gather evidence to test it, we won't know if this is actually the case (no matter how much we want to believe it.) A rather simple experiment for this: a horse race. If another horse outraces it, then the hypothesis is falsified.

This procedure is called the "hypothetico-deductive method", and is basically what experiments in Science are all about. To put it in its basic form "If you were wrong, how would you know it?"

Note that part of developing a good experimental design is actually phrasing your hypothesis properly. For example, we might be interested in the presence of fossils of ceratopsids (horned dinosaurs, like Triceratops) in rocks the last 15 million years of the Cretaceous Period in continental Africa. If we state our hypothesis "there were latest Cretaceous African ceratopsids", than how many observations do we need to make to demonstrate this is true? Does a single observation with negative results show us there is no ceratopsids in latest Cretaceous Africa? No. How about ten negative results? A thousand? Until we have excavated all latest Cretaceous rocks from Africa, we cannot demonstrate that there are no ceratopsids. However, by stating the hypothesis as "there were no ceratopsids in latest Cretaceous Africa", then a single positive observation of a ceratopsian is all we need to confidently overturn (falsify) this hypothesis.

The above is an example of employing a null hypothesis. The null represents a form of the hypothesis that must be rejected before we even accept a phenomenon exists. If we cannot reject the null hypothesis, there is no reason to think that the phenomenon in question is worth considering. If, instead, we find we can reject the null (in the instance above, finding a latest Cretaceous ceratopsid in Africa), than we can go on and examine the situation in more detail.

The hypothetico-deductive method shows that we can confidently reject hypotheses, but that we cannot "prove" them in an absolute philosophical sense. As the number of observations and experiments which fail to reject an hypothesis increases, we can be more and more confident in its truth. However, ideas in Science are only provisionally accepted: that is, we often use statistical measures of confidence (plus/minus readings, error bars, and other demonstrators of degree of support). Uncertainty is a staple part of Science. However, some ideas are so overwhelmingly well-supported that to reject them at present is perverse: these are what we call "facts". (Similarly - using the example above - if we made many excavations in latest Cretaceous continental African rocks and continuously failed to uncover ceratopsid fossils but find plenty of other dinosaurs, we will provisionally reject the idea of African horned dinosaurs, but recognize that a single fossil could overturn this rejection.)

The following (from Thomas Kida's Don't Believe Everything You Think) are a useful set of characteristics for thinking like a scientist:

• Keep an open mind, but be skeptical of any unsubstantiated claim
• Make sure a claim (hypothesis) can be tested
• Evaluate the quality of the evidence for a claim
• Try to falsify the hypothesis (i.e., look for discomfirming evidence)
  • Observations of natural phenomena lead to possible explanations (hypotheses)
  • These hypotheses must be falsifiable (i.e., there must be some test, experiment, or observation which can demonstrate that the hypothesis is untrue)
  • Until the hypothesis is tested, it is only considered a speculation
  • If the hypothesis survives a test (or tests) of falsification, it is tentatively (or provisionally) accepted (keeping in mind that additional tests might potentially overturn the hypothesis)
• Consider alternative explanations (we call these "multiple working hypotheses")
• Other things being equal, choose the claim that is the simplest explanation for the phenomenon (i.e., the one that requires the fewest assumptions)
  • This is formally known as the principle of parsimony, and also called Occam's razor
• Other things being equal, choose the claim that doesn't conflict with well-established knowledge
  • This is sometimes referred to as the principle of consilience
• Proportion your acceptance of a claim to the amount of evidence for or against a claim

Historical Sciences
Something worth noting concerning the issue of paleontology, historical geology, evolutionary biology, astronomy, and other sciences which are concerned primarily with events which have already happened: i.e., historical sciences. These are concerned with actual particular events and cases just as much as general patterns (as opposed to, say, particle physics or organic chemistry, where all collisions of the same particles or folding of the same protiens are identical). As a consequence, although we can perform some kinds of experiments or observations under controlled circumstances to duplicate the past conditions, in general we are looking at evidence of the past event.

That doesn't make it any less scientific, nor does it dismiss the ability to do repeatable observations. "Repeatability" in this case is where different observers--or the same observer in multiple different examinations--can make the same observations of the same set of data. (For example, if a scientist asserts that a particular layer of clay shows an enriched abundance of the metal iridium, consistent with an asteroid impact, other scientists can sample the same layer and look for this material, and the original research can resample the material to test that it is there.)

There is a cliché that paleontologists are a kind of "detective", and that isn't a bad comparison. Much like forensics experts in crime scene investigations or medical examiners, we examine a series of data to develop a hypothesis (or multiple hypotheses) to explain the observations at hand, and test these hypotheses against both the currently-known data and additional relevant data we look for.

In general, it is best to follow Carl Sagan's "Baloney Detection Kit":

However, just because something is a theory doesn't mean it is an accurate map of how the Universe really operates. A scientific theory is more specifically a comprehensive framework for describing, explaining, and making falsifiable predictions about related sets of phenomena based on rigorous observation, experimentation, and logic. Scientific theories are not necessarily correct (that is, accurate maps of the Universe), but before we accept them they should at least match our current observations.

A key element of both theories and hypotheses is that they are predictive: that is, by using them you can make estimates before hand about observations not yet done. In the case of historical sciences like paleontology and geology, "predictions" don't necessarily mean "what things will be like in the future", but rather "what will we be likely to discover about a past event, which we have not yet examined".

Contrary to some statements (even by reputable scientific organizations), scientific theories are not limited to describing only large scale ("universal") phenomena nor ongoing phenomena. Thus, "one time" only events (such as the impact theory of the extinction at the end of the Cretaceous or the Big Bang at the beginning of spacetime) or phenomena limited in scope (such as the theory of thermohaline circulation as the major driver of modern climate, or again of the impact cause of the Cretaceous extinction) are indeed subject to theory, and these theories can be explored and tested via parsimony, fecundity, consilience, auxilary hypotheses, and so forth. Nevertheless, the most important (and most fecund) theories ARE about large-scale ongoing phenomena: atomic theory of matter; periodic theory of the elements; special relativity; the germ theory of disease; the theory of evolution by means of natural selection; plate tectonic theory of geology; and so on.

It is very common to find that in certain spheres of Science there are multiple different (and sometimes mutually exclusive) theories proposed for the same observations. Indeed, this is what a lot of scientific research is about: the creation of and testing of new theories and their auxiliary hypotheses. Hence there are fields like theoretical physics in which new models of the operation of the universe and its various components are proposed and assembled based on previous observations, logic, conjecture, and speculation. Other scientists (experimental physicists, observational astronomers, etc.) themselves look for observations that could in principle reject some or all of the components of these theories. This research involves creating sets of experiments whose results will be different under different alternative theories about the phenomenon involved. We can test and reject theories in part in the same fashion as we do hypotheses: that is, by parsimony, consilience, and by tests of falsification.

But what about scientific laws? Popular accounts of the scientific method suggest a hierarchy of observation -> hypothesis -> theory -> law, but this is not correct. The phrase "scientific law" in the Sciences was largely been abandoned in the 20th Century. Many of the traditional "scientific laws" were simply scientific theories that can be rendered as mathematical equations. As a consequence they tend to deal with relatively simple and more easily measurable phenomena. "Scientific laws" were thus no better nor worse than other scientific theories at withstanding rejection: for example, Bode's law of planetary orbital distance wound up being a coincidence more than a law; Newton's laws of motions only apply to certain gravitational conditions and speeds; and so forth. "Scientific laws" can be useful in some circumstances (e.g., calculating gas pressure, volume, temperature, or number of particles given the other variables using the ideal gas law PV = nRT), but there are many realms of Science where the phenomena are too complicated to be reduced at present to law-like forms. This holds true of much of geology, climatology, biology, and especially behavioral sciences. So be very careful if you hear from someone who proposes some "law" of biology or paleontology or anthropology or psychology!

There is a subset of theories that have withstood substantial repeated tests and modifications and survived if not unscathed, at least strongly supported and the victor against all challengers so far. These include (but aren't limited to) the atomic theory of matter; the theory of evolution by means of Natural Selection; plate tectonics theory; the germ theory of disease; etc. We honestly don't have a good term to distinguish these theories from the more run-of-the-mill, still-in-play types. (One might suggest facts, and there is some merit there, but a "fact" might be a better synonym for a well-substantiated observation rather than an entire theory.) The British evolutionary biologist Richard Dawkins proposed (in 2009) using the new word theorum for this class of theories. Time will tell if this nomenclature will catch on.

Regardless of what we call them, we can describe this collection ideas as theories which are to the best of our knowledge "true", but this requires the caveat that absolute "Truth" is empirically impossible to find (although it would be extraordinarily perverse to reject these things as being "true" in a general sense without some extraordinary new evidence to the contrary.) These winning theories can be thought of as the all-time prize-winning champions in their respective fields, having faced and defeated all challengers. In principle (indeed, "in theory"! :-) they could be defeated by a newcomer, but the weight of evidence so far is with the champions.

On the other hand, many scientific questions (especially technical and precisely phrased ones concerning matters which we can have access to the appropriate observation) have correct answers: that is, they are not matters of opinion (as are questions in a great many of other fields).

Not all viewpoints are equally valid in Science:

• That is, a viewpoint is only considered valid when measured against the natural world, and not by any other metric (seniority of proposer; how well it matches a personal, political, religious, or other belief, etc.)
• Therefore, "compromise" positions between different viewpoints are no more likely to be valid than "extreme" positions. Support for a position is ascertained against the natural world.

Concepts within science are subject to change with new discoveries. That is in fact what scientists DO for a living: make new discoveries!!

• Consequently, scientific discoveries are provisional and subject to future refinement (or sometimes even rejection)
• The scientific enterprise thus entails not only successful discoveries, but many failures along that way that scientists should take with quiet dignity and grace

Often, people ask "what do scientists believe." This is the wrong question! Science is not about belief; it is about discoveries and about the methods by which those discoveries were made and tested.

Through Science, we have discovered many aspects of nature. Here are some of the largest level aspects (finer details would be those covered by different content disciplines):

• Nature is understandable; we can achieve an effective understanding of nature through the application of reason and critical thinking
• Natural phenomena tend to follow regular patterns expressible in mathematics (i.e., "laws" in the sense of many physics problems), although these patterns often become increasingly difficult to phrase mathematically for more complex phenomena
• Nature is mechanistic (i.e., it follows regular laws and patterns), but not deterministic (because many phenomena are stochastic and probabilistic, and therefore cannot be predicted in advance)
• In Nature, not all things are possible
• Also, not all possible things happen (e.g., a coin could land "heads" or "tails", but will only do one of those two possible results when actually flipped)
• Consequently, many things in nature only make sense when you understand both the processes that generate the patterns, AND the patterns themselves

"Part 2: Testing, testing 1-2-3" (2:30):

"Part 3: Blinded by Science" (2:45):

"Part 4: Confidently Uncertain" (3:01):

"Part 5: Do the right thing" (2:38):

"Part 6: Citizen Science" (3:34):

Why write & publish papers?

• Disseminate results
• Claim priority for ideas (specific publication dates allowed a verifiable and agreed-upon date for when ideas were established)
• Provide evidence for claims (allowing for others to attempt at verification/falsification)
• Set up ideas of additional lines of research; implications
• And more

• Periodicals of particular professional societies
• These might be be weekly, monthly, or on even longer schedules, depending on the scope of the science involved
• Some societies (such as the American Association for the Advancement of Science, the British Association for the Advancement of Science, the Royal Society of London, the National Academy of Sciences of the United States of America, etc., cover the entire field of natural, physical, and social sciences.
• But other societies might be much narrower in scope
• Bulletins, conference proceedings, or other less-regular publications (published on special occasions--a particular conference, perhaps--or when a sufficient number of acceptable manuscripts have been gathered)
• Chapters in an edited volume on a particular topic from a technical or university press
• Entire books from a technical or university press
• Self-published in a non-technical press: once far more common, now relatively rare

Scientific papers might be very short (1-2 pages), or monographs (dozens to hundreds of pages long), but most are typically between 4 and a few dozen pages long. Monographs are primarily used to thoroughly document a single particular topic: a complete description of the anatomy and biology of a particular species or group of species; a review of the geography or the geology of a particular region; the results of a particular space probe; etc.: in other words, topics with a large amount of observations in a very narrow topic. Very short papers tend to simply announce a new discovery, document an important new observation, or respond to a particular criticism of previous work. The middle range papers are where most the hypothesis testing goes on.

It was once very common to have single-authored papers, or maybe just two authors. These have become fairly rare, and it is common to find papers with a half-dozen or more authors. In fact, in some cases there can be dozens of contributing authors!

How are scientific papers assembled and published? In general, they follow the pattern here:

• Do the initial research, taking observations, measurements, etc.
• Plot up the graphs, charts, tables, etc. that allow one to test an idea
• Write up the text that explains what was observed, what was tested, what the results were, what it implies, etc.
• Submit the paper for review. In some cases the paper may have been specifically requested by the editors of a journal or book. In most cases, however, it is submitted by the author(s) directly to the editor of an appropriate journal.
• After an initial review by the receiving editor (at which point it might be rejected: for example, if it is blatantly unscientific or if it is on a topic not covered by that journal), the editor sends it out to one or more (often two or three) professionals in the field for peer-review
  • Peer-review is one of the hallmarks of scientific analysis. It is typically "blind" (the authors never know who the reviewers are, although they can sometimes suggest appropriate experts), although not typically "double blind" (that is, it is typical for the reviewers to know who the authors are, although some journals actually do make sure that they are double-blind reviews).
  • The peer-reviewers do a critical analysis of the manuscript: are the methods sound? Does it take into account previous work on the subject? Are the conclusions justified by the analytical results? Etc.
  • The peer-reviewers provided a write-up of their analysis, and their opinion as to whether the paper is acceptable, should be rejected, or might be accepted given certain revisions. This write-up is sent back to the editors of the journal.
• The journal editor takes into account all the critical reviews by the peer-reviewers, and makes a decision to reject, accept, or accept with revisions. On some occasions the editor may send a revised manuscript back to the original reviewers for a second review, or they may use an entirely new team of reviewers.
• If rejected, the authors might submit the manuscript to an entirely different journal, and the whole process starts over again
• If accepted, it is put into the publication queue and eventually makes it into print. Typically a published paper includes the date of submission and the date of acceptance so that other workers in the field have a sense of when these ideas and results were first obtained.

• Title of the paper (which should give the reader an idea of what it is about)
• The author(s) and their contact information (institutional affiliation and postal and e-mail addresses)
• An abstract: a short (typically 1-2 paragraph) long section that states the basic problem/issue, the most critical observations, and the fundamental conclusions of the paper. (Let's face it: except for someone actually doing research in the field, it is most likely that the abstract of a paper is the only part that anyone is going to read in any detail.)
• An introduction and background: sometimes the same single section, sometimes split into separate sequential parts. Examines what issue is of concern, and previous work in the subject. It is in this part that the hypothesis/hypotheses to be tested are established.
• Methods & Materials: what analytical techniques and observations are going to be made, and upon what material (specimens) those techniques are going to be made
• Results: when the methods were applied to the materials, what was discovered? Was the hypothesis supported or rejected? With what level of confidence? While plots, charts, and tables may be present in other sections of the paper, they are the "bread-and-butter" of the results section!
• Discussion: given the results, what does it imply for this field of study? What does it suggest about previous ideas on the subject? What implications does it have for future research in this field?
• Conclusions: summary of the results and the discussion. Typically only a paragraph or two long. (The casual reader will likely read the Abstract in detail, skim the middle, look at the figures in the Results, and read the Conclusions in detail.)
• Acknowledgments: typically one-to-two paragraphs, thanking those who contributed to the study but who were not authors (for example, those who might have allowed access to data). Also typically specific reference to funding agencies who lent support to the project, often by listing the number of the specific grant(s) involved.
• Bibliography of those references specifically cited in the text. Unlike books or some other works, only those references which are specifically cited are listed.

The above description reviews the basic components of a scientific technical paper. There are other sorts of publications in the scientific world which some might confuse for a research report. It is important to bear in mind that these other items are NOT technical research papers, and as such do not have the same weight in terms of their importance in the world of science. In general, these other forms of publication are not tests of hypotheses or reports of new observations. Here are some examples, listed roughly in decreasing order of "significance" in terms of their standing as scientific papers:

• Review papers: these often have the same general properties as a scientific technical research paper with one major exception: they are not announcements of new discoveries nor new analyses of data. Instead, reviews are summaries of the current state of research in a particular field. They typically do not give new analytical results or tests of hypotheses. However, they have an important role as places where different papers (often by many different researchers, perhaps but not necessarily the present one) are synthesized into a whole. They are also extremely useful in finding the original research (as references) in a particular field. Review papers are sometimes included within the typical scientific journal (and if so are normally indicated as such). Additionally, there are entire journals (e.g., the huge line of Annual Reviews journals; the Quarterly Review of Biology; etc.) which are entirely review papers.
• Conference abstracts: these are "proto-papers" in a sense: one-to-two paragraph overviews of the work presented at a technical conference (either as a stand-up platform presentation or as a poster). Oftentimes these presentations are the seeds of a future publication. But because just the abstract is presented, and because neither the data nor the analyses yet been subjected to peer-review, they are not regarded as "finished works" in the scientific community. They are occasionally cited in technical research papers because they serve as documents as to when a particular idea or discovery was first presented to the scientific world. However, when the full research article is published, it is that rather than the conference abstract which is regarded as the "real" analysis.
• Commentary: these are labeled as such (or with a special name, such as the "News & Views" section of Nature or the "Perspectives" section of Science). These are normally reviews of a particular technical paper (or perhaps multiple papers) in that issue of the journal, in which a different expert in the same subject is asked to present the important broader implications of that technical paper. In addition to the having a special designation, you can recognize a commentary by: having slightly less "jargony" text, as it is there to translate the highly technical language of the original article into something a non-specialist might appreciate, and; by indicating (typically in the first two paragraphs) the specific article(s) later in that issue which are being discussed.
• News reports: many journals will give short reports announcing the publication, results, and implications of significant new technical publications. These might be papers later in the issue of that journal, or they might be in entirely different journals. News reports can be distinguished from technical research reports (and indeed all the over types of articles already discussed) in that they a) often have no specific author listed; b) are very short (maybe just a single paragraph); c) normally have no references, except for the journal article that is being reported; d) do not show any actual analysis.
• Editorial: some--although by no means all--scientific journals may have an occasional editorial or opinion piece. These are indicated as "Editorial" or "Opinion," and consist of an editor's (or invited author's) thoughts, comments, and opinions on some pressing topic. These almost never have new analytical results, and will typically only have a few references (compared to an actual research article). These are useful to find out what particular editors think about various policies and subjects, but are not scientific results as such.
• Press releases: these might be press releases from the home institution of a researcher, or a granting agency, or a corporation, or many other subjects. In the case of the first two, it is typical for the home institution of a researcher and an agency supporting a particular grant to put out a press release at the same time that important new technical research publications are published. (This is for a number of reasons, not least of which is to justify to the shareholders in that institution that their money is being put to good and productive use!) Note that these press releases are not subject to independent peer review, and consequently are not considered valid references by the scientific community. Their primary value is to communicate with the media and the general public. Similarly public or private institutions and corporations may put out press releases on particular scientific topics. They might be useful in terms of presenting data not otherwise available (e.g., the statistics and measurements of a particular piece of scientific equipment, for instance), and so might be cited in that context. However, analytical results and observations in these are again not subject to independent peer review, and are thus potentially suspect.

Throughout the rest of the program--and indeed, the rest of your academic career--keep these thoughts in mind when evaluating whether a paper you might encounter might be a real technical research report, some other type of scientific account, or something else entirely.

A final note: is peer-review perfect? Of course not, and no one claims that it is! However, the existence of at least this level of checks-and-balance means that scientific technical research reports have had to face a level of criticism that nearly all other forms of publication (news articles, press releases, political tracts, etc.) never have to do before they see the light of day. This is the first main step in the self-correcting nature of Science.

The next main step? If you believe that a previous research article is in error (because of difference in interpretation of methods or observations, or new data that you have uncovered), then you are free to write up a new paper incorporating your new thoughts, and submit it to the same scrutiny. And thus the process continues: what is technically referred to as "reciprocal illumination."

How to Read a Scientific Paper

The above gives you a sense of how scientific research (and other type) papers are constructed. But how should you, as a user of said papers, go about reading them?

One recent tend in undergraduate scientific literacy education is the "C.R.E.A.T.E" approach. This has to do not so much with reading the paper per se, but with attitudes to take when approaching reading science. This (admittedly forced, as are most such things) acronym stands for:

• Consider the topic
• Read the paper itself
• Elucidate the hypotheses. That is, determine precisely what the authors were trying to test.
• Analyze and interpet the data. In other words, see how they tested the hypotheses, whether they were effective in doing so, what conclusions they made from it, etc.
• and Think of the next Experiment. Nearly all scientific studies result in new lines of research being opened up; think about how one would then approach those new questions.

The stereotyped approach to reading a paper is "abstract, then conclusion, then the stuff in between if you are interested in it". This obviously isn't the way the papers are organized, and is a bit unfair to the researchers' work, but at least it is very quick. However, this is by no means the only way. For instance, here is an essay and here a number of perspectives about different approaches to reading a paper. (And here is a more cautionary tale...)

As with most written documents, there is no one single proper way to read them. Find what works best for you.

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Another Relevent Video
"Introduction to Scientific Journal Literature" (put together by the library of Dalhousie University in Canada):

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Last modified: 30 July 2020