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Record W7084415036 · doi:10.60825/h4wg-dx41

Pre-Season Run Size Forecasts for Fraser River Sockeye Salmon (Oncorhynchus nerka) in 2024

2025· report· en· W7084415036 on OpenAlexaff

Bibliographic record

VenueFisheries and Oceans Canada / Pêches et Océans Canada - Publications · 2025
Typereport
Languageen
FieldEnvironmental Science
TopicFecal contamination and water quality
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsPacific decadal oscillationSea surface temperatureSubmarine pipelineProductivityPacific oceanForecast period

Abstract

fetched live from OpenAlex

Forecasts for the 2024 Fraser River Sockeye and Pink salmon returns were prepared with Bayesian statistical models and presented as cumulative probability distributions. The total Fraser River Sockeye return for 2024 has a median estimate of 567,000 (80% PI:167,000 to 2,173,000) expected mainly from the Chilko and Harrison River stocks in the Summer run timing group. Forecasts for 8 stocks included environmental covariates while sibling models were used to calculate the age-5 forecast for 6 stocks. Nearshore sea surface temperature suggest mixed environmental signals for salmon productivity while the Pacific Decadal Oscillation suggests that sea surface temperatures offshore are more favourable. The 2024 Pre-season Fraser Sockeye forecast represents the lowest forecast on record, with the next lowest being on the same cycle line in 2024.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.739
Threshold uncertainty score0.520

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.002

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 head0.022
GPT teacher head0.250
Teacher spread0.229 · 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 designSimulation or modeling
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

Citations0
Published2025
Admission routes1
Has abstractyes

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