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Record W6957855727 · doi:10.60825/tmjh-hx79

Coastal ecological survey of fishes in western Coronation Gulf, Nunavut

2019· report· en· W6957855727 on OpenAlexaffabout

Bibliographic record

VenueFisheries and Oceans Canada / Pêches et Océans Canada - Publications · 2019
Typereport
Languageen
FieldSocial Sciences
TopicRegional Development and Environment
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsHabitatSalvelinusArctic charClupeaForage fishArcticCoronation

Abstract

fetched live from OpenAlex

A survey of coastal fishes was conducted in western Coronation Gulf in the fall of 2017 in order to assess community composition of nearshore fishes and identify their habitat associations. Fishes were collected at coastal sites in close proximity to the Rae (67°55' N and 115°20' W), and Coppermine (67°49' N and 115°05' W) rivers, near the community of Kugluktuk, Nunavut from September 1st to 7th , 2017. This report summarizes species occurrences, basic biological information for captured individuals, and the environmental characteristics at their locations of capture (i.e., depth, total dissolved solids, and temperature). Overall, 14 species were collected (total fish collected n = 96) in which Arctic Cisco (Coregonus autumnalis (Pallas, 1776)) and Saffron Cod (Eleginus gracilis (Tilesius, 1810)) were most abundant. The composition of species represent both marine-associated (e.g., Pacific Herring; Clupea pallasii Valenciennes, 1847) and freshwater-associated (e.g., Lake Trout, Salvelinus namaycush (Walbaum, 1792)) fishes where the Coppermine and Rae rivers enter the Coronation Gulf. Preliminary collection of baseline data to assess marine fish habitats will contribute to the development of a monitoring plan for nearshore ecosystems. Linking this work to studies of Arctic Char (Salvelinus alpinus (Linnaeus, 1758)) will enable assessment of habitat usage across marine and freshwater ecosystems that are used by subsistence fishes and co-occurring 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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.058
GPT teacher head0.270
Teacher spread0.212 · 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

Citations0
Published2019
Admission routes2
Has abstractyes

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