The determination of maturity stages in male elasmobranchs (Chondrichthyes) using a segmented regression of clasper length on total length
Bibliographic record
Abstract
A novel statistical method for estimating the stages of maturity in male sharks and skates based on a segmented regression (SRM) is proposed. We hypothesize that this method is able to find the transition points in the three-phase relationship between total length (TL) and clasper length (CL). We applied an SRM to TL–CL data of nine species, from large pelagic sharks (e.g., Carcharhinus falciformis) to small coastal skates (e.g., Rioraja agassizi), captured in the southwestern Atlantic and northeastern Pacific. As expected, SRM detected two breakpoints, defining three maturity stages (immature, maturing, and mature), in six out of nine species. For three species, it was not possible to find two breakpoints because of incomplete sampling of TL. This novel method is noninvasive, it is applicable to previously collected data, is easy to use, and provides a reliable tool for increasing our understanding of elasmobranch reproductive strategies.
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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 | 0.002 |
| 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) | 0.000 | 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".