The anatomy of the jawless fish head and the early evolution of vertebrates
Bibliographic record
Abstract
No other structure better characterizes vertebrates than the head, with its intricate nervous innervations, highly specialized muscles, and massive skull. Did the first vertebrate possess all of those traits, or did early vertebrates acquire them in steps? Answers may lie in the jawless grade of vertebrates. Based on dissections, a histological analysis, and μCT imaging of cartilages, muscles, and nerves in hagfish and lampreys, I demonstrate that the biomechanics of jawless vertebrate head differs from that of jawed vertebrates in two distinct ways: linear muscle antagonism and elastic recoiling of the skeleton. I report structures in both hagfish and lampreys that either represent precursors to jawed vertebrate conditions (e.g., cardinal heart foreshadowing synovial joints; replacement of tooth plates mimicking that of the true teeth) or appear to be intermediate between two distinct tissues of jawed vertebrates (e.g., a cartilage functionally acting as a skeletal element but histologically identical to tendons). Evolutionary precursors to the jawed vertebrate conditions appeared in steps and transformed quickly at the origin of jaws. Coupled with the molecular genetic evidence, I present an evolutionary scenario for early vertebrates in which expression of the mandibular‐patterning Dlx pathway shifts via a series of specializations in feeding and respiratory structures. Grant Funding Source : NSERC
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".