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Record W2167619624 · doi:10.1093/icesjms/fsm037

Application of the precautionary approach and conservation reference points to management of Atlantic seals

2007· article· en· W2167619624 on OpenAlexafffundabout
Mary Hammill, Garry B. Stenson

Bibliographic record

VenueICES Journal of Marine Science · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsFisheries and Oceans Canada
FundersFisheries and Oceans Canada
KeywordsPopulationResource (disambiguation)Environmental resource managementMarine conservationBusinessPrecautionary principleNatural resource economicsGeographyEnvironmental planningComputer scienceEnvironmental scienceEconomicsEcologyBiology

Abstract

fetched live from OpenAlex

Abstract Hammill, M. O., and Stenson, G. B. 2007. Application of the precautionary approach and conservation reference points to management of Atlantic seals. – ICES Journal of Marine Science, 64: 702–706. Resource management requires a trade-off between conservation, economic, and political concerns in establishing harvest levels. The precautionary approach (PA) brings scientists, resource managers, and stakeholders together to identify clear management objectives and to agree on population benchmarks that would initiate certain management actions when those benchmarks are exceeded. A conceptual framework for applying the PA to marine mammals is outlined. For a data-rich species, precautionary and conservation reference levels are proposed. When a population falls below the precautionary reference level, increasingly risk-averse conservation measures are applied. A more conservative, risk-averse approach is required for managing data-poor species. The framework has been implemented for the management of commercial seal harvests in Atlantic Canada.

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)0.002
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 score0.085
Threshold uncertainty score0.170

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.022
GPT teacher head0.266
Teacher spread0.244 · 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

Citations48
Published2007
Admission routes3
Has abstractyes

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