Length conversions and mass–length relationships of five forage‐fish species in the California current ecosystem
Bibliographic record
Abstract
Abstract Length‐measurement conversions and seasonal mass–length relationships (MLR) for Pacific herring Clupea pallasii, northern anchovy Engraulis mordax, Pacific sardine Sardinops sagax, Pacific mackerel Scomber japonicus and jack mackerel Trachurus symmetricus in the California Current are presented. The conversions between total (LT), fork (LF,) and standard lengths (LS) should facilitate comparisons of data across disciplines and institutions. These equations resulted from an analysis of measurements spanning 14 years and the western seaboard of North America, from the north end of Vancouver Island to the USA–Mexico border. Major‐axis regressions were used to calculate reciprocal length‐measurement conversions (e.g., LT to LS and LS to LT) and generalised linear models and ordinary least‐squares models were used to create MLRs that account for seasonal variations. The MLR models indicated seasonal differences for all species except C. pallasii, for which there was no multi‐season data. Discrepancies between these and published models were examined, along with the suitability and benefit of the various types of models used for length‐measurement conversion and MLRs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".