Mandibular premolar and second molar root morphological variation in modern humans: What root number can tell us about tooth morphogenesis
Bibliographic record
Abstract
This investigation of modern human mandibular premolar root variation tests the hypothesis that population-specific mandibular single-rooted premolar root size can predict a predisposition to root morphological complexity. Mandibular postcanines were examined and quantified from dental radiographs in a globally spread sample of 1,615 modern humans. Multirooted premolars and a fused molar root phenotype were investigated as probes into greater than, and less than, the normative root number. Twelve questions were addressed concerning root structure of mandibular premolars and second molars. A direct correlation was found between single-rooted mandibular premolar size and the predisposition to multirootedness. This correlation infers the following: 1) that postcanine primordia size during root formation predisposes to the development of more, or less, than the normative postcanine root number; and 2) that the epigenetic effect of tooth primordium size per se influences the induction of interradicular processes, which divides the root during its development. This simple developmental model helps explain the following observations: 1) population-specific variation in postcanine root number; 2) sexual dimorphism for multirooted mandibular premolar prevalence; 3) why microdont teeth are single-rooted; 4) the hierarchy of developmental canalization of interradicular processes; 5) megadont-hominin to late-hominin mandibular premolar root number transition; and 6) the fluctuation of mandibular premolar root number in primate evolutionary history.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".