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Record W2186568604 · doi:10.1139/cjfas-2012-0236

Effects of ice on behaviour of juvenile Atlantic salmon (<i>Salmo salar</i>)

2013· article· en· W2186568604 on OpenAlexafffundvenue
Tommi Linnansaari, Richard A. Cunjak

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of New Brunswick
FundersNorges ForskningsrådCanada Research Chairs
KeywordsSalmoNocturnalHoming (biology)Period (music)JuvenileFisheryEnvironmental scienceBiologyFish <Actinopterygii>Ecology

Abstract

fetched live from OpenAlex

The behaviour of Atlantic salmon (Salmo salar) parr was compared among three periods of winter (pre-ice period, PI; period of subsurface ice, SSI; period of surface ice, SI). Salmon parr remained nocturnal regardless of the ice conditions. The level of nocturnal activity was similar during PI and SI periods but was significantly reduced during the SSI period. Immobility was also highest during the SSI period, but was only partly attributable to salmon parr being trapped under ice. No differences in daytime activity among ice periods were observed. Two nocturnal movement tactics were observed: (i) “emerge–settle–return” and (ii) “emerge–move–return”. The tactics were used similarly during PI and SSI periods, but the “move” tactic was predominant during the SI period. Atlantic salmon parr showed a strong tendency to return to their “home stone” after a period of activity. Homing was reduced during the SSI period, but the distance moved to a new home stone was typically <10 m. In general, salmon parr were able to cope well with subsurface and surface ice.

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 score0.993
Threshold uncertainty score0.013

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 head0.008
GPT teacher head0.193
Teacher spread0.185 · 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

Citations18
Published2013
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic Sciences→Same topicFish Ecology and Management Studies→French-language works237,207→