MétaCan
Menu
Back to cohort
Record W2125599484 · doi:10.1139/f00-134

Predation on hatchery-reared lobsters released in the wild

2000· article· en· W2125599484 on OpenAlexvenueno aff
Gro van der Meeren

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicCrustacean biology and ecology
Canadian institutionsnot available
Fundersnot available
KeywordsPredationFisheryBiologyGadusHatcheryCarapaceSculpinCannibalismEcologyCrustaceanFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Predation on hatchery-reared lobsters (Homarus gammarus) in the wild was studied in order to identify predators in southwestern Norway on rocky and sandy substrates in winter and summer. Lobsters of 12-15 mm carapace length were tagged with magnetic microtags. About 51 000 juvenile lobsters were released on 10 occasions at three locations. Predator samplings were by trammel nets, eel traps, and videorecordings during the 24 h immediately following the releases. In summer, loss to predators occurred on both rocky and sandy substrates. The loss was lower in winter when lobsters were found as prey in predators caught on sand. The risk of fish predation was highest in the first hours after release, when the lobsters were out of shelter. The wrasses Labrus bergylta and Labrus mixtus were the major predators of lobsters, while Atlantic cod (Gadus morhua), shorthorn sculpin (Myoxocephalus scorpius), and crab (Cancer pagurus) were mainly winter predators. Winter predators were never as abundant as summer predators. To minimise predatory loss of reared and costly lobsters, they should be released onto rocky substratum in winter. Due to the damage to the predated lobsters, it was not possible to correlate survival against lobster size.

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)0.001
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 score0.989
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.016
GPT teacher head0.204
Teacher spread0.188 · 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

Citations46
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic SciencesSame topicCrustacean biology and ecologyFrench-language works237,207