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Record W6950598751 · doi:10.5683/sp3/80jdbu

Data on black spot disease occurence in fish communities of lakes from Québec, Canada

2024· dataset· en· W6950598751 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueBorealis · 2024
Typedataset
Languageen
FieldArts and Humanities
TopicLibraries and Information Services
Canadian institutionsUniversité du Québec à Trois-RivièresUniversité de Montréal
Fundersnot available
KeywordsMinnowLittoral zoneFish <Actinopterygii>Black spotTransectHabitatCensus

Abstract

fetched live from OpenAlex

This dataset is the result of a collaborative study on spatial ecology of the black spot disease in fish communities from the littoral zone of lakes located in Saint-Hippotyle, QC, Canada. Sampling occurred during summer 2022. Black spot occurence was assessed in fish samples through either minnow traps, seine nets or observational snorkeling transects. This data describe fish community matrix, infected fish community matrix and their environment. Habitat description and water chemistry measurements are given for transect samples. Geographical and morphometric lake attributes are also given.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.005
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.049
GPT teacher head0.236
Teacher spread0.187 · 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