MétaCan
Menu
← Back to cohort
Record W2011619377 · doi:10.1139/f00-218

Depth-dependent vertebral number of Atlantic cod (<i>Gadus morhua</i>) on the Magdalen Shallows and Scotian Shelf: stock mixing or microgeographic trends within populations?

2000· article· en· W2011619377 on OpenAlexvenueno aff
Douglas P. Swain, Kenneth T. Frank

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
Fundersnot available
KeywordsGadusAtlantic codOceanographyFisheryGadidaeGeographyBiologyFish <Actinopterygii>Geology

Abstract

fetched live from OpenAlex

We examined spatial variation in the vertebral number of Atlantic cod (Gadus morhua) during the summer feeding season in the southern Gulf of St. Lawrence and on the Scotian Shelf. Mean vertebral number increased significantly with depth in the southern Gulf and on the northeastern Scotian Shelf but not on the southwestern Scotian Shelf. In the southern Gulf, where sampling was most extensive, mean vertebral number increased steadily as depth increased from 25 m to over 175 m. Mean vertebral number was also strongly related to relative length within age-classes, with the larger fish at age having more vertebrae. However, the association between vertebral number and depth could not be attributed to confounding between depth and size at age. These results indicate either unexpected mixing between neighbouring cod populations or unexpected structure at fine spatial scales within cod populations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.943
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.033
GPT teacher head0.255
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic Sciences→Same topicMarine and fisheries research→French-language works237,207→