Regular anatomical terms revisited: The simplest is often the right one
Bibliographic record
Abstract
Regular anatomical (RA) terminology rules were developed to simplify and clarify Latin anatomical terms in a systematic manner. These rules, which prohibit conjunctions, prepositions, and appositions, and define a consistent word order pattern, are extensions of the original 1895 rule of anatomical nomenclature that anatomical terms should be as short and simple as possible. It is not coincidental that most terms in Terminologia Anatomica (TA), and many traditional terms that were not used in TA, are consistent with RA term rules, and that the RA term rules are also consistent with the guidelines for expanding short form terms to full, unique terms. The consistent form of RA terms facilitates learning and translation, and is easier for humans and machines to manipulate than terms that are not compliant with RA term rules. Despite assertions to the contrary, RA terms are proper Latin terms that simplify the anatomical terminology and, in many cases, restore traditional terms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; both teacher heads agree on what is shown here.
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".