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Record W2147136303 · doi:10.1016/s1054-3139(03)00022-5

Ocean thermal conditions in the post-smolt nursery of North American Atlantic salmon

2003· article· en· W2147136303 on OpenAlexaff
Kevin D. Friedland, David G. Reddin, Martín Castonguay

Bibliographic record

VenueICES Journal of Marine Science · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsFisherySea surface temperatureHabitatAbundance (ecology)Stock (firearms)PredationEnvironmental scienceOceanographyClimate changeGeographyBiologyEcologyGeology

Abstract

fetched live from OpenAlex

Abstract The effect of climate on the post-smolt survival of North American Atlantic salmon is obscure owing to the difficulty in interpreting the only relationships thus far observed between the abundance of these stocks and climate, which focuses on winter conditions. Placing significance on winter post-smolt survival is contrary to conventional thinking that the spring period is more important, because that is when the post-smolts migrate to sea and transition to ocean life takes place. The pre-fishery abundance for North American stocks was compared to thermal conditions in potential post-smolt nursery areas during the period 1982–1999. Pre-fishery abundance was modeled as a reconstruction of one-sea-winter (1SW) and two-sea-winter (2SW) age salmon populations. Cohort abundance was compared to mean temperature and thermal habitat (sea surface area within a given temperature range) in five index areas. Stock size was negatively correlated with mean sea surface temperature during June. Correlations were comparatively stronger between stock abundance and thermal habitat, further asserting that June conditions – the first month at sea for most stocks in the region – may be pivotal to survival. These correlations suggest that post-smolt survival is negatively affected by the early arrival of warm ocean conditions in the nursery area. Hypotheses related to post-smolt migration, predation, and the availability of suitable prey are discussed.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.022
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.006
GPT teacher head0.229
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 teacher head, 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

Citations68
Published2003
Admission routes1
Has abstractyes

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