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Record W2312930845 · doi:10.1080/17451000.2012.678858

Physical characteristics of persistent deep-water spawning sites of capelin: Importance for delimiting critical marine habitats

2012· article· en· W2312930845 on OpenAlexafffundabout
Paulette M. Penton, Gail K. Davoren

Bibliographic record

VenueMarine Biology Research · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCapelinForage fishMallotusDemersal zoneHabitatFisheryPredationDemersal fishEcologyOceanographyBiologyEnvironmental scienceFish <Actinopterygii>Geology

Abstract

fetched live from OpenAlex

In coastal Newfoundland, high abundances of top predators aggregate (biological hotspots) over deep-water (demersal) spawning sites of capelin (Mallotus villosus), the focal forage fish on which most top predators rely for prey. We explore the mechanisms underlying the spatial persistence of hotspot formation by investigating physical characteristics associated with the persistent use of demersal spawning sites of capelin on the northeast Newfoundland coast from 2003 to 2010. The continued presence of suitable spawning sediment (0.5–16 mm) in permanent bathymetric depressions was a key determinant of site use persistence, whereas minimum temperature (~2°C) influenced the use of sites with suitable sediments. We suggest that biological hotspots associated with demersal spawning sites with similar physical characteristics could be used to delineate critical marine habitats for protection throughout the circumpolar distribution of this key forage fish species.

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 score0.121
Threshold uncertainty score0.241

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.074
GPT teacher head0.362
Teacher spread0.288 · 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

Citations33
Published2012
Admission routes3
Has abstractyes

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