MétaCan
Menu
Back to cohort
Record W2099653221 · doi:10.1016/j.icesjms.2004.12.005

Possible ecosystem impacts of applying MSY policies from single-species assessment

2005· article· en· W2099653221 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueICES Journal of Marine Science · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsUniversity of British Columbia
FundersNational Science Foundation
KeywordsMaximum sustainable yieldFishingEcosystemSustainable yieldEnvironmental scienceVariety (cybernetics)FisheryFisheries managementEcologyEnvironmental resource managementBiologyStatisticsMathematics

Abstract

fetched live from OpenAlex

Abstract Ecosim models have been fitted to time-series data for a wide variety of ecosystems for which there are long-term data that confirm the models' ability to reproduce past responses of many species to harvesting. We subject these model ecosystems to a variety of harvest policies, including options based on harvesting each species at its maximum sustainable yield (MSY) fishing rate. We show that widespread application of single-species MSY policies would in general cause severe deterioration in ecosystem structure, in particular the loss of top predator species. This supports the long-established practice in fisheries management of protecting at least some smaller “forage” species specifically for their value in supporting larger piscivores.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.237
Threshold uncertainty score0.995

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 communication0.0000.002
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.026
GPT teacher head0.291
Teacher spread0.265 · 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