Replication Data for: Effects of body size and environmental region on the nutritional value of small pelagic species in the California Current
Bibliographic record
Abstract
This dataset contains all raw nutritional data from calorimetry and proximate composition analysis of small pelagic species in the California Current Large Marine Ecosystem (CCLME) used to undertake analyses for this publication. This manuscript examines nutritional variation across individuals sampled from April - October 2021 for five species: northern anchovy (Engraulis mordax), market squid (Doryteuthis opalescens), bigfin lanternfish (Symbolophorus californiensis), boreal clubhook squid (Onychoteuthis borealijaponica), and pyrosomes (Pyrosoma atlanticum). The raw data includes individual energy density, lipid, protein, and moisture content, length, weight, and spatiotemporal information. Column header descriptions are provided in a separate metadata table. This dataset is a part of the Pelagic Species Trait Database (https://doi.org/10.5683/SP3/0YFJED), which we encourage users to explore for nutritional information from a broader range of species, years, and geographic regions. We ask researchers and students to contact us to discuss applications of this data. Please reach out to (stephanie.green@ualberta.ca) to discuss collaboration opportunities and data integration.
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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 | 0.005 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.258 | 0.141 |
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".