Bibliographic record
Abstract
The sum of all possible bite forces along a mammalian tooth row is related to the area under the curve when bite force is plotted from one end of the tooth row to the other. Integrating the equation of this plot and dividing by the length of the entire jaw, from joint to incisor, gives the average bite force along the entire jaw (as opposed to along the tooth row). Calculations indicate that for any jaw shape there is only one location for the tooth row relative to the midline of the skull, where the average bite force is maximized; the average force is lower when the tooth row is closer to, or farther from, the midline. In addition, for animals with long narrow jaws, the location where this maximum is realized is relatively closer to the midline than it is for animals with short wide jaws. In many mammals, the distance between the jaw joints (jaw width) often varies between 60 and 80% of the distance from the jaw joints to the incisor (jaw length) in narrow and wide jaws, respectively. Length is measured perpendicular to the resultant force of the jaw muscles. Accepting that average bite force will be maximized, the model predicts that in the longer, narrower jaws the distance between the two molar rows will be approximately half the width of the jaw (and will approach 60% in the shorter, wider jaws).
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".