Bibliographic record
Abstract
Q UR knowledge of any subject never goes beyond col- lecting observations and forming some half-conscious expectations, until we find ourselves eonfronted with some experience eontrary to those expectations.This at onee rouses us to consciousness; we turn over our reeolleetions of observed facts; we endeavour so to rearrange them, to view them in such new perspective that the unexpected experience shall no longer appear surprising.This is what we call explaining it, which always eonsists in supposing that the surprising facts that we have observed are only one part of a larger system of facts, of whieh the other part has not come within the field of Dur experience, whieh larger system, taken in its entirety, would present a certain character of reasonableness, that indines us to accept the surmise as true, or likely.For example, let a person entering a large room for the first time, see upon a wall pro j ecting from behind a large map that has been pinned up there, three-quarters of an admirably executed copy in freseo of one of RafaePs most familiar cartoons.In this instance the explanation flashes so naturally upon the mind and is so fuHy accepted, that the spectator quite forgets how surprising those facts are which alone are presented to his viewj namely, that so exquisite a reproduetion of one of Rafael's grandest eompositions should omit one-quarter of it.He guesses that that quarter is there, though hidden by the map; and six months later he will, maybe, be ready to swear that he saw the whole.This will be a case under alogicopsychicallaw of great importance, to which we may find occasion to revert so on, that a fuHy aceepted, simple, and interesting inference tends to obliterate aH reeognition of the un-(267 )
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.008 | 0.017 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.145 | 0.061 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".