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Discrimination of family‐specific odours by juvenile coho salmon: roles of learning and odour concentration*

2001· article· en· W2145665807 on OpenAlexaff
Simon C. Courtenay, Thomas P. Quinn, Hélène Dupuis, C. Groot, Peter Larkin

Bibliographic record

VenueJournal of Fish Biology · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsFisheries and Oceans CanadaUniversity of British Columbia
Fundersnot available
KeywordsJuvenileBiologyAttractivenessPreferenceZoologyOncorhynchusChemical communicationEcologyFisheryPsychologySex pheromoneFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Free‐swimming coho salmon fry Oncorhynchus kisutch of some families showed preference (relative to the behaviour of naïve sibs) for the odours of similarly aged non‐sibs to whom they had been exposed during the post‐hatch (alevin) stage and the early free‐swimming (fry) stage, but not the embryo (egg) stage, indicating that odour‐learning had occurred during the later developmental periods. Recognition (i.e. preference) of sib‐ pecific odours was evident after a month, and in one case 5 months, of separation from those odours. Thus, young salmon incubating in their gravel nests in streams appear to have the capacity to learn the chemical characteristics of conspecifics and retain this memory for at least several months without reinforcement. However, in addition to the general attractiveness of sibs and familiar non‐sibs over unfamiliar non‐sibs, some non‐sibs were consistently more attractive than others. Preference between two different non‐sib odours could be reversed by changing their relative concentrations, indicating that relative attractiveness is a function of both familiarity and odour concentration. Therefore, although juvenile coho salmon learn, remember, and are subsequently attracted by sib‐specific odours in early life, familiar odours are not always preferred over unfamiliar conspecific odours. Preference in dyadic assays is therefore an insensitive measure of recognition.

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)0.000
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 score0.034
Threshold uncertainty score0.261

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.017
GPT teacher head0.242
Teacher spread0.225 · 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

Citations41
Published2001
Admission routes1
Has abstractyes

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