✍ Scribed by Swanson, Don R.
No coin nor oath required. For personal study only.
This study demonstrates that certain unintended logical connections within the scientific literature, connections potentially revealing of new knowledge, are unmarked by reference citations or other bibliographic clues. Specifically, 25 biomedical articles central to the argument that dietary fish oil causes certain blood changes are compared with 34 articles on how similar blood changes might ameliorate Raynaud's disease. The two groups of articles are thus connected by a chain of reasoning implicitly suggesting that dietary fish oil might benefit Raynaud patients, an hypothesis not heretofore published explicitly. By retrieving and bringing together these two literatures, that implicit, unstated, and perhaps unnoticed hypothesis becomes apparent. The more general problem is posed of whether systematic search techniques for bringing together logically connected literatures can be developed and described, in the hope of discovering other implicit, unstated hypotheses. The example analyzed shows that the problem, while solved in this case by trial-and-error search methods, may be inherently and peculiarly difficult because there are virtually no references in either literature to the other, nor are there any clues from cocitation, bibliographic coupling, or statistical association of descriptors that the two literatures are logically related.
In order to make clear my use of the language of science, I shall state, without defending, a few presuppositions. Empirical scientific theories, even if well established, cannot be known with certainty to be "true," for no theory can be tested under all possible conditions; any such theory might someday be overthrown by a sufficiently severe test that it fails. Empirical theories are always hypotheses; they are conjectures about a putative reality of which we can have no certain or immediate knowledge. All empirical knowledge is forever conjectural, though some hypotheses, theories, or conjectures are better tested, more widely accepted, and so
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