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Record W2589016411 · doi:10.1139/cjfas-2016-0414

High-resolution seafloor mapping to describe coastal denning habitat of a Canadian species at risk: Atlantic wolffish (<i>Anarhichas lupus</i>)

2017· article· en· W2589016411 on OpenAlexafffundvenueabout
Emilie Novaczek, Rodolphe Devillers, Evan Edinger, Luiz G.S. Mello

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsFisheries and Oceans CanadaMemorial University of Newfoundland
FundersFisheries and Oceans Canada
KeywordsHabitatBathymetryFisheryBayGeographyOceanographyEcologyBiologyGeology

Abstract

fetched live from OpenAlex

The Atlantic wolffish (Anarhichas lupus) is listed by Canada’s Species at Risk Act as a species of special concern. Effective conservation strategies rely on accurate knowledge of habitat requirements, distribution, and vulnerabilities; however, current management plans cite lack of wolffish habitat data as a key limitation. For this study, coastal Atlantic wolffish denning habitat was characterized and mapped with high-resolution multibeam data and seafloor video in Conception Bay, Newfoundland. Four Atlantic wolffish dens, used for feeding, spawning, and egg-guarding, were surveyed and mapped. On the basis of the geomorphology and substrate of these dens, a supervised classification was applied to the multibeam bathymetry and backscatter data to identify other potential denning areas. Predicted denning habitat, limited by the occurrence of suitable rocky substrate, is most prevalent in shallow waters (<22 m) distributed over 1.6 km2 (5.9%) of the study area. Shallow denning habitat is exposed to seasonal maximum temperatures that exceed the threshold for normal Atlantic wolffish egg development, a potential vulnerability for nearshore wolffish. As management efforts progress, this information will guide research and prioritization of conservation areas.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score0.348

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.036
GPT teacher head0.223
Teacher spread0.186 · 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

Citations19
Published2017
Admission routes4
Has abstractyes

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