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Behaviour and thermal experience of adult sockeye salmon migrating through stratified lakes near spawning grounds: the roles of reproductive and energetic states

2009· article· en· W2124228141 on OpenAlexafffund
David Roscoe, S. G. Hinch, Steven J. Cooke, D. Patterson

Bibliographic record

VenueEcology Of Freshwater Fish · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsSimon Fraser UniversityFisheries and Oceans CanadaCarleton UniversityUniversity of British Columbia
FundersFisheries and Oceans CanadaNatural Sciences and Engineering Research Council of CanadaBC Hydro
KeywordsOncorhynchusEnergeticsEcologyBiologyReproductive successFisheryFish <Actinopterygii>Energy expenditureThermoregulationEnvironmental scienceDemography

Abstract

fetched live from OpenAlex

Roscoe DW, Hinch SG, Cooke SJ, Patterson DA. Behaviour and thermal experience of adult sockeye salmon migrating through stratified lakes near spawning grounds: the roles of reproductive and energetic states. Ecology of Freshwater Fish 2010: 19: 51–62. © 2009 John Wiley & Sons A/S Abstract – Little is known about physiological factors underlying thermal behaviour in Pacific salmon (Oncorhynchusspp.). We implanted acoustic transmitters and temperature loggers into migrating adult sockeye salmon (Oncorhynchus nerka) and nonlethally assessed their reproductive hormone levels and energetic states immediately prior to their passing through natal lakesen routeto spawning grounds. We tested the hypothesis that energetic and reproductive status influence thermoregulatory and other in‐lake behaviours. More reproductively advanced females with lower levels of energy transited through cooler temperatures compared to less mature females with high levels of energy, possibly to reduce metabolic energy expenditure and delay final maturation. Transit temperatures of males were not related to physiological variables. Salmon travelled on average 13.6 km·day−1through two lakes, and often circled or held for more than 1 day before moving upstream, but these behaviours were generally not related to physiological variables.

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 score0.005
Threshold uncertainty score0.010

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 head0.007
GPT teacher head0.215
Teacher spread0.208 · 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

Citations60
Published2009
Admission routes2
Has abstractyes

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