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Record W2146538963 · doi:10.1139/f06-162

Tracking seasonal migrations of redfish (<i>Sebastes</i> spp.) in and around the Gulf of St. Lawrence using otolith elemental fingerprints

2007· article· en· W2146538963 on OpenAlexvenueaboutno aff
Steven E. Campana, Alexandra Valentin, Jean‐Marie Sévigny, Don Power

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
Fundersnot available
KeywordsSebastesOtolithFisheryOceanographyFish <Actinopterygii>BiologyGeology

Abstract

fetched live from OpenAlex

Large concentrations of beaked redfish (Sebastes mentella and Sebastes fasciatus) overwinter in the Cabot Strait and the approaches of the Gulf of St. Lawrence each year. Synoptic research vessel surveys indicate that redfish are distributed more widely in the summer than in the winter, particularly within the Gulf. Significant differences in the trace element composition of the otolith ("otolith elemental fingerprint") were observed among summer aggregations, indicating that the aggregations maintained some degree of separation while in the Gulf. Sebastes mentella and S. fasciatus were readily distinguished based on otolith elemental fingerprints. Using the elemental fingerprints of the summer samples as a natural tag, we found that S. mentella tended to move out of the Gulf in the winter. Aggregations of S. mentella found in the east during the summer were not found in our winter collections. The elemental fingerprints of S. mentella from the Saguenay Fjord were clearly distinct from redfish further east in the Gulf of St. Lawrence, indicating that this group had been separated from other redfish for much of their life. The implications of our findings extend not only to the fisheries management of redfish, but also to the extent of movement expected of deepwater fish species.

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 score0.789
Threshold uncertainty score0.419

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.032
GPT teacher head0.261
Teacher spread0.228 · 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

Citations50
Published2007
Admission routes2
Has abstractyes

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