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Behaviour, growth and survival of redfish larvae in relation to prey availability

2001· article· en· W1991305011 on OpenAlexaff
Benjamin J. Laurel, Jennifer Brown, Rebekah L. Anderson

Bibliographic record

VenueJournal of Fish Biology · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsFisheries and Oceans CanadaMemorial University of Newfoundland
Fundersnot available
KeywordsPredationBiologyGadusLarvaSebastesIchthyoplanktonFisheryForage fishLimitingForageZoologyFish <Actinopterygii>Ecology

Abstract

fetched live from OpenAlex

Growth, survival and condition of redfish larvae Sebastes spp., reared in the laboratory (0, 500 1500 and 4500 prey l‐1) were highest in the 1500 prey l‐1 treatment. Significantly lower larval growth and survival in the 4500 prey l‐1 treatment corresponded with lower prey bite: orient ratios in later weeks, suggesting that larvae were unable to forage efficiently at high prey densities. While these prey densities are higher than those reported in the field, naturally co‐occurring Atlantic cod Gadus morhua larvae require higher prey densities when reared under similar conditions in the laboratory. These data suggest that prey availability may not be as limiting to redfish as for other commercially important marine species.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

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 head0.020
GPT teacher head0.271
Teacher spread0.250 · 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

Citations38
Published2001
Admission routes1
Has abstractyes

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