Estimation of mortality of juvenile blacktip sharks, <i>Carcharhinus limbatus,</i> within a nursery area using telemetry data
Bibliographic record
Abstract
A population of young blacktip sharks (Carcharhinus limbatus) was monitored over three years to determine their mortality rates using a series of acoustic listening stations. Based on these data it was possible to use several mortality estimators, including indirect life history based methods and direct methods such as the Kaplan-Meier and SURVIV methods, to estimate natural, fishing, and total mortality. Kaplan-Meier (6191%) and SURVIV (6292%) methods provided nearly identical total mortality rates during the first six months of life. This agreement suggests that these estimates are accurate for this population. All natural and fishing mortality occurred within the first 15 weeks of the study. This suggests that young sharks are most vulnerable to all types of mortality during this period. Sharks that survived beyond the first 15 weeks successfully left the nursery and were presumed to have migrated southward during fall months. These results provide critical information concerning the early life history of sharks and the importance of nursery areas to the survival of young animals.
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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 | 0.000 | 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 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".