Solar zenith angles for biological research and an expected catch model for diel vertical migration patterns that affect stock size estimates for longfin inshore squid (<i>Doryteuthis pealeii</i>)
Bibliographic record
Abstract
Solar zenith angles are useful in diel studies because they are directly related to potential solar irradiance at the point of sampling and can be calculated from location, date, and time of day. We used zenith angles to quantify diel vertical migration effects on both the probability of a positive tow and catch size for longfin squid (Doryteuthis pealeii) using two-stage generalized additive models (GAMs). Zenith angles were better than time of day for modeling diel effects on inshore longfin squid bottom trawl survey catches and were particularly suitable for data collected over large areas and extended time periods. Diel effects were size-specific in most cases. Our expected catch method can be used to account for diel effects when estimating swept-area stock size from research survey data. Differences in observed day–night catches and model results show the potential for bias in swept-area stock size estimates that ignore diel migration effects. Zenith angles may be useful in specifying prior distributions for survey catchability parameters in stock assessment models.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".