The principles of anatomical nomenclature revision: They're more like guidelines anyway
Bibliographic record
Abstract
Revision of the international standard anatomical terminology is required periodically to add names for new entities, delete archaic terms, and correct errors in existing terms. In addition to a small set of nomenclature rules, three principles have guided revisions: names should not be changed unless they are wrong; corrections of perceived errors should not be pedantic; and inclusion of every minor structure should not be attempted. These principles have served well, and are expected to continue to do so, but they have also proven to be subjective because their application through the history of the international terminology has varied. Specific efforts to deal with existing problems and new organizational initiatives to prevent future issues are presented. Clin. Anat. 33:327-331, 2020. © 2019 Wiley Periodicals, Inc.
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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 | 0.057 | 0.102 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.004 | 0.026 |
| Scholarly communication | 0.014 | 0.018 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.008 | 0.024 |
| Insufficient payload (model declined to judge) | 0.009 | 0.021 |
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".