Quantifying changes in umbilicus size to estimate the relative age of neonatal blacktip reef sharks (<i>Carcharhinus melanopterus</i>)
Bibliographic record
Abstract
ABSTRACT Sharks can incur a range of external injuries throughout their lives that originate from various sources, but some of the most notable wounds in viviparous shark neonates are at the umbilicus. Umbilical wounds typically heal within 1 to 2 months post-parturition, depending on the species, and are therefore often used as an indicator of neonatal life stage or as a relative measure of age [e.g. grouping by umbilical wound classes (UWCs), according to the size of their umbilicus]. To improve comparisons of early-life characteristics between studies, species and across populations, studies using UWCs should integrate quantitative changes. To overcome this issue, we set out to quantify changes in umbilicus size of neonatal blacktip reef sharks (Carcharhinus melanopterus) around the island of Moorea, French Polynesia, based on temporal regression relationships of umbilicus size. Here, we provide a detailed description for the construction of similar quantitative umbilical wound classifications, and we subsequently validate the accuracy of our classification and discuss two examples to illustrate its efficacy, depletion rate of maternally provided energy reserves and estimation of parturition period. A significant decrease in body condition in neonatal sharks as early as twelve days post-parturition suggests a rapid depletion of in utero-allocated energy reserves stored in the liver. Back calculations of timing of birth based on the umbilicus size of neonates determine a parturition season from September to January, with most parturitions occurring during October and November. As such, this study contributes valuable data to inform the conservation and management of young-of-the-year blacktip reef sharks, and we therefore encourage the construction and use of similar regression relationships for other viviparous shark species.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 teacher head, 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".