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Record W2786283620 · doi:10.1139/facets-2017-0069

The biology and ecology of slimy sculpin: A recipe for effective environmental monitoring

2018· article· en· W2786283620 on OpenAlex
Michelle A. Gray, R. Allen Curry, Tim J. Arciszewski, Kelly R. Munkittrick, Sandra M. Brasfield

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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueFACETS · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsWilfrid Laurier UniversityAlberta EnergyUniversity of New Brunswick
Fundersnot available
KeywordsSculpinEcologyFish <Actinopterygii>Environmental changeBiologyCottusFisheryGeographyEnvironmental resource managementClimate changeEnvironmental science

Abstract

fetched live from OpenAlex

Recently, the use of small-bodied fish in environmental monitoring has increased, particularly within the Canadian environmental effects monitoring (EEM) and other adaptive programs. Although it is possible to measure changes with many small-bodied species, interpretation is often complicated by the absence of information on the biology and ecology of fish not of commercial, recreational, or traditional interest. Knowing and understanding the basic biology of these fishes aids in the sensitivity of study designs (i.e., ability to detect change) and the interpretation of all biological levels of responses (e.g., cellular to community). The increased use of slimy sculpin ( Cottus cognatus Richardson, 1836) in impact assessment studies in North America provides a considerable amount of information on life history aspects. The slimy sculpin has the most ubiquitous North American distribution among cottids but yet has a very small home range, thus integrating environmental conditions of localized areas. This paper describes aspects of slimy sculpin life cycle that affect collection efficiency and timing, and describes and provides data collected over more than 10 years of studies at more than 20 reference study sites. This overview provides a functional and informative compilation to support adaptive environmental monitoring and provide a baseline for comparative ecological study.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.290

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 studies0.0000.001
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 head0.007
GPT teacher head0.248
Teacher spread0.241 · 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