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Record W6996382357

Risk assessment of permitted human activities in Rockfish Conservation areas in British Columbia

2020· report· en· W6996382357 on OpenAlexaboutno aff

Bibliographic record

VenueArchimer (Ifremer) · 2020
Typereport
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsRockfishMarine protected areaGroundfishFishingRisk assessmentMarine conservationCoral reefBaseline (sea)
DOInot available

Abstract

fetched live from OpenAlex

The Government of Canada has committed to reaching domestic marine conservation targets (MCTs) of protecting 10% of Canada’s marine and coastal areas by 2020. One area of action that supports reaching Canada’s MCTs is the identification and advancement of “other effective area based conservation measures” (OEABCM). To determine whether Rockfish Conservation Areas (RCAs) in Canada’s Pacific marine waters contribute to the MCTs as OEABCMs, RCAs were evaluated against the five criteria for inclusion as OEABCMs. In 2016, an internal evaluation of RCAs by DFO determined that a more fulsome review was required, including a risk assessment to assess whether permitted human activities inhibit RCAs from meeting criterion 5. To this end, a literature review of RCA documents provides evidence that RCAs align with OEABCM criteria 1 through 3, while greater clarity that RCAs will be in place for a long-term duration is required to meet criterion 4. A Level 1 qualitative risk assessment was conducted to assess RCAs against OEABCM criterion 5. The assessment was conducted on three significant ecosystem components: Inshore Rockfish, their Prey and Rocky Reef habitat, and the impact of twenty-one currently permitted activities. Eight activities were identified as having the potential to prevent RCAs from fulfilling the OEABCM criteria: outfalls, Crab by Trap, coastal infrastructure, oil spill, Prawn and Shrimp by Trap, FSC dual fishing groundfish hook and line, movement and storage of logs, and finfish aquaculture. Future assessments at the scale of individual RCAs will provide clarity regarding the impacts of stressors in each RCA. Recommendations include: developing clear long-term conservation and/or stock management objectives; collecting empirical observations of habitat in RCAs; improving research and monitoring efforts to reduce uncertainties about activities with highest relative risks; and improving fishery monitoring and catch reporting of sectors fishing inside RCAs.

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)0.008
metaresearch head score (Gemma)0.021
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 score0.111
Threshold uncertainty score0.299

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0100.011
Science and technology studies0.0030.002
Scholarly communication0.0050.001
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.043
GPT teacher head0.323
Teacher spread0.280 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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