Bomb dating, age validation and quality control of age determinations of monodontids and other marine mammals
Bibliographic record
Abstract
Methods for confirming the accuracy of age determination methods are reasonably well established in fishes, but the millions of routine age determinations which take place every year require their own quality control protocols. In contrast, methods for ensuring accuracy in age determination of monodontids and other marine mammals are still being developed. Here we review the basis and application of bomb radiocarbon to marine mammal age validation, highlighting its value for providing unambiguous estimates of age for belugas and other long-lived animals which form growth bands. Bomb radiocarbon is particularly useful for marine mammals, given that the age of an individual animal can be determined to within ±1-3 years, as long as it was alive during the 1960s. However, ongoing age determinations require careful monitoring to ensure that age interpretations remain consistent across ages and through time. Quality control protocols using reference collections of ageing material, in conjunction with age bias plots and measures of precision, are capable of detecting virtually all of the systematic ageing errors that often occur once age determinations of an animal become routine.
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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 | 0.021 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".