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Record W2544569106 · doi:10.1071/pc15029

Prevalence of interactions between Hawaiian monk seals (Nemonachus schauinslandi) and nearshore fisheries in the main Hawaiian Islands

2016· article· en· W2544569106 on OpenAlexaboutno aff
Kathleen S. Gobush, Tracy A. Wurth, J.R. Henderson, Brenda L. Becker, Charles L. Littnan

Bibliographic record

VenuePacific Conservation Biology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
Fundersnot available
KeywordsFisherySeal (emblem)PopulationGeographyFisheries scienceQuarter (Canadian coin)Fur sealFisheries managementFishingBiologyDemographyArchaeology

Abstract

fetched live from OpenAlex

We determine the prevalence and characteristics of interactions between the Hawaiian monk seal (Nemonachus schauinslandi) and nearshore fisheries in the main Hawaiian Islands and examine impacts to the subpopulation. We documented 139 monk seal–fisheries interactions between 1976 and 2014: 132 hookings typically involving large circle hooks accompanied by slide-bait rigging, and 7 gill-net entanglements. We individually identified 297 monk seals between 1988 and 2014 and recorded that 83 (28%) of these had at least one documented hooking or entanglement. Most individuals were aged two years or younger and a quarter of them were hooked or entangled multiple times. Documented fisheries interactions typically occurred at a monk seal’s natal island and most frequently on Kauai and Oahu. Fisheries interaction was directly implicated in 11 monk seal deaths and was slightly higher in frequency than other known mortality factors. The proportion of monk seals alive one year after a documented fisheries interaction varied by age class and ranged between 76% and 84%. Survival one year later for monk seals with a documented fisheries interaction versus matched controls (all age classes combined) was not significantly different. Nonetheless, fully understanding the scale and impacts of fisheries interactions, as well as mitigating these impacts, is important if the monk seal population of the main Hawaiian Islands is to maintain a positive growth trajectory.

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 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 score0.041
Threshold uncertainty score1.000

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)0.0010.000

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 head0.030
GPT teacher head0.260
Teacher spread0.230 · 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.

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

Citations8
Published2016
Admission routes1
Has abstractyes

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