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Record W6888771633 · doi:10.21966/c7na-z171

Juvenile Salmon Migration Dynamics in the Discovery Islands and Johnstone Strait; 2015–2017

2015· dataset· en· W6888771633 on OpenAlexaff

Bibliographic record

VenueHakai Institute · 2015
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsJuvenileAbundance (ecology)Period (music)Relative species abundance

Abstract

fetched live from OpenAlex

In this report, we analyze migration dynamics of sockeye salmon in the Discovery Islands to Johnstone Strait region based on purse seine data collected by the Hakai Institute Juvenile Salmon Program from 2015–2017. The majority of out-migrating juvenile Fraser River salmon (Oncorhynchus spp.) pass northwest through the Strait of Georgia, the Discovery Islands, and Johnstone Strait. The Discovery Islands to Johnstone Strait leg of the migration is a region of poor survival for sockeye salmon (Oncorhynchus nerka) relative to the Strait of Georgia. High-resolution spatiotemporal measurements of migration timing and abundance of juvenile sockeye salmon and the relative species composition of co-migrating juvenile salmon are needed to understand the factors influencing early marine survival through this region. The peak migration period in the Discovery Islands in which 50 % of sockeye passed through occurred between May 25 and June 4 and in Johnstone Strait between May 30 and June 12. Peak abundance was observed earlier than normal in 2015 and 2016, likely due to anomalously warm winter and spring weather. Sockeye migrated at 2.0 BL•s-1 between the Discovery Islands and Johnstone Strait based on the peak migration date in each region, faster than the 1.1 BL•s-1 observed in the Strait of Georgia. Sockeye abundance was much lower in 2017 compared to 2015 and 2016. Species composition was dominated by sockeye in 2015 and 2016, and by chum (Oncorhynchus keta) in 2017.

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)0.001
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: Dataset · Consensus signal: none
Teacher disagreement score0.106
Threshold uncertainty score0.211

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.027
GPT teacher head0.296
Teacher spread0.269 · 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
GenreDataset

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

Citations1
Published2015
Admission routes1
Has abstractyes

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