<scp>I</scp>ntrinsic <scp>C</scp>onstraints on the <scp>D</scp>iversification of <scp>N</scp>eotropical <scp>C</scp>ichlid <scp>A</scp>dductor <scp>M</scp>andibulae <scp>S</scp>ize
Bibliographic record
Abstract
The diversification of functional traits may be constrained by intrinsic factors, such as structural, mechanical, developmental, or physiological limitations. We explored the biomechanical and constructional constraints on the size of the major jaw closing muscles, the adductor mandibulae complex (AM), in a diverse clade of freshwater fish - the Neotropical cichlids. Using phylogenetic comparative methods, we contrasted patterns of size variation and diversification rates of three AM divisions with variables describing head size and biomechanical coefficients describing force and velocity transmission. We found that all three AM muscles examined were impacted by constructional constraints, namely, (1) the space available in the head (head length and width-all AMs), (2) competition with the eye (AM1 and AM2), (3) competition for space among the three major AM divisions (e.g., AM1 vs. AM3), and (4) potentially the shape of the lower jaw (AM2). Only AM2 size was significantly associated with lower jaw biomechanical coefficients, but opposite predictions based on force transmission (i.e., no compensation for low mechanical advantage). Diversification rates of the mass of the divisions of the AM were also not connected to the diversification rates of their biomechanical coefficients. Previously suggested compensation in AM mass for reduced force transmission among ram-feeding predators appears to be driven by overall body plan changes (lengthening of the head in elongate bodies) and only indirectly to biomechanical trade-offs. Strong constructional constraints on AM size likely limit potentially functional morphospace occupation, and highlight the highly integrated nature of ram-suction feeding functional adaptations in Neotropical cichlids. Anat Rec, 301:216-226, 2018. © 2018 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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".