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Record W4223639060 · doi:10.1139/as-2021-0022

Coastal marine biodiversity in the western Canadian Arctic

2022· article· en· W4223639060 on OpenAlexafffundvenueabout
Miranda Bilous, Darcy McNicholl, Karen M. Dunmall

Bibliographic record

VenueArctic Science · 2022
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsFisheries and Oceans Canada
FundersDirectorate for Biological SciencesUniversity of WaterlooUniversity of Manitoba
KeywordsBiodiversityArcticBenthic zoneTrophic levelGeographyMarine ecosystemClimate changeEcosystemFisheryEcologyEnvironmental scienceOceanographyAbundance (ecology)Biology

Abstract

fetched live from OpenAlex

Establishing a baseline of Arctic marine biodiversity is necessary for monitoring impacts of climate change in the vulnerable Canadian Arctic and protecting sensitive regions that are of significant importance to Inuit culture and socioeconomics. Under the goals of improving documentation of Arctic marine communities and creating a tool for assessing coastal Arctic biodiversity across different regions, relative abundance data of fishes, benthic invertebrates, and prey items found in fish stomach contents from coastal areas near Paulatuk and Sachs Harbour, Northwest Territories, and Kugluktuk, Nunavut were used to calculate Shannon–Wiener Biodiversity Indices. Biodiversity varied among and within regions and trophic groups; fish and stomach content biodiversity were highest in Kugluktuk, whereas benthic biodiversity was highest near Paulatuk. The methods presented here can be used as a tool for assessing low- to mid-trophic Canadian Arctic coastal biodiversity and would also facilitate spatial comparisons and long-term monitoring as climate warming impacts Arctic ecosystems.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient 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 score0.065
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0120.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.046
GPT teacher head0.331
Teacher spread0.285 · 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

Citations6
Published2022
Admission routes4
Has abstractyes

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