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Record W2126931445 · doi:10.1139/f05-134

Spatial variability in rockfish (<i>Sebastes</i> spp.) recruitment events in the California Current System

2005· article· en· W2126931445 on OpenAlexvenueno aff
John C. Field, Stephen Ralston

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
Fundersnot available
KeywordsSebastesRockfishSpatial ecologyFisherySpatial variabilityTemporal scalesBiologyScorpaenidaeEcologyGeographyFish <Actinopterygii>Statistics

Abstract

fetched live from OpenAlex

A general assumption regarding spatial patterns of recruitment variability is that species with similar early life history characteristics tend to covary in reproductive success over scales of 500–1000 km. These assumptions are based on evaluation of recruitments from independent stocks, as few studies have assessed synchrony in recruitment within broadly dispersed stocks over finer spatial scales. We used data on age composition and landings to generate regional time series of recruitment deviations for three species of rockfish in the California Current System (Sebastes goodei, Sebastes entomelas, and Sebastes flavidus). We then used correlation analysis, principal components analysis, and other methods to evaluate the degree of synchrony among recruitment events in these regions. Results show that 51%–72% of the year-to-year variability in recruitment is shared coastwide within these species, while a lesser but significant fraction of the variability is associated with finer scale geographic features.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.057
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.037
GPT teacher head0.260
Teacher spread0.223 · 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

Citations39
Published2005
Admission routes1
Has abstractyes

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