It’s elemental, my dear Watson: validating seasonal patterns in otolith chemical chronologies
Bibliographic record
Abstract
Accurate age data are essential for reliable fish stock assessment. Yet many stocks suffer from inconsistencies in age interpretation. A new approach to obtain age makes use of the chemical composition of otoliths. This study validates the periodicity of recurrent patterns in 25Mg, 31P, 34K, 55Mn, 63Cu, 64Zn, 66Zn, 85Rb, 88Sr, 138Ba, and 208Pb in Baltic cod (Gadus morhua) otoliths from tag–recapture and known-age samples. Otolith P concentrations showed the highest consistency in seasonality over the years, with minima co-occurring with otolith winter zones in the known-age otoliths and in late winter – early spring when water temperatures are coldest in tagged cod . The timing of minima differs between stocks, occurring around February in western Baltic cod and 1 month later in eastern Baltic cod; seasonal maxima are also stock-specific, occurring in August and October, respectively. The amplitude in P is larger in faster-growing western compared with eastern Baltic cod. Seasonal patterns with minima in winter – late spring were also evident in Mg and Mn, but less consistent over time and fish size than P. Chronological patterns in P, and to a lesser extent Mg and Mn, may have the potential to supplement traditional age estimation or to guide the visual identification of translucent and opaque otolith patterns used in traditional age estimation.
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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 | 0.018 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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".