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Record W6976899824 · doi:10.60825/0hzg-nm96

Survey of Northern Abalone in British Columbia’s PFMAs 3 and 4, May 2021

2025· report· en· W6976899824 on OpenAlexaffabout

Bibliographic record

VenueFisheries and Oceans Canada / Pêches et Océans Canada - Publications · 2025
Typereport
Languageen
Field
Topic
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsAbaloneQuadratJuvenileHabitatEndangered species

Abstract

fetched live from OpenAlex

The Northern abalone (Haliotis kamtschatkana) is a marine mollusc that is patchily distributed along the west coast of Canada. A moratorium on harvest was put in place in 1990 after severe declines in abundance. In 2011, Northern abalone was designated as endangered under Schedule 1 of the Species at Risk Act (SARA). Fisheries and Oceans Canada (DFO) has conducted index site surveys for Northern abalone since 1978, rotating through five regions along the BC coast. In May 2021, an exploratory abalone survey was conducted in previously un-surveyed portions of Pacific Fishery Management Areas (PFMA) 3 and 4 in the North Coast of British Columbia. Estimated mean density of abalone (emergent; all sizes) was 3.43 abalone/m2, 95% CI [2.77, 4.32]. Emergent juvenile abalone (20 – 69 mm Shell Length (SL)) were most abundant (2.82 abalone/m2, 95% CI [2.23, 3.69]) followed by emergent adult abalone (70 mm – 99 mm SL; 0.39 abalone/m2, 95% CI [0.28, 0.54]) then emergent large adults (≥ 100 mm SL; 0.01 abalone/m2, 95% CI [0.01, 0.03]). Estimated mean density of cryptic abalone (all sizes) was 0.23 abalone/m2, 95% CI [0.12, 0.39]. The proportion of sites with large adults (≥ 100 mm SL) present was 14.3% and the proportion of quadrats containing mature (≥ 70 mm SL) abalone was 23.6%. These results were compared to the most recent index site surveys conducted in Northern BC and to recovery goals, objectives, and targets set for Northern abalone in the Action Plan.

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: Other · Consensus signal: none
Teacher disagreement score0.040
Threshold uncertainty score0.080

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 studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.025
GPT teacher head0.234
Teacher spread0.210 · 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
GenreOther

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

Citations0
Published2025
Admission routes2
Has abstractyes

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Same venueFisheries and Oceans Canada / Pêches et Océans Canada - PublicationsFrench-language works237,207