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Record W2122355889 · doi:10.22621/cfn.v122i3.606

Habitat Use by the Eastern Sand Darter, <em>Ammocrypta pellucida</em>, in Two Lake Champlain Tributaries

2008· article· en· W2122355889 on OpenAlexvenueaboutno aff
Shannon M. O’Brien, Douglas E. Facey

Bibliographic record

VenueThe Canadian Field-Naturalist · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersNature Conservancy
KeywordsSubstrate (aquarium)TributaryRiffleHabitatEtheostomaThreatened speciesEndangered speciesSTREAMSEnvironmental scienceRange (aeronautics)CobbleEcologyFisheryGeographyFish <Actinopterygii>Biology

Abstract

fetched live from OpenAlex

The Eastern Sand Darter (Ammocrypta pellucida) is endangered or threatened throughout much of its range, which includes the St. Lawrence-Lake Ontario drainage of southern Ontario and Quebec and several Vermont tributaries of Lake Champlain. The species is known for its tendency to burrow, and field observations have suggested that habitat use may depend on substrate particle size. To determine whether Eastern Sand Darter densities were correlated with substrate particle size, fish and substrates were sampled in 156 plots in two Vermont rivers during the summers of 2001 and 2002. The Eastern Sand Darter occurred mainly in areas in which substrate composition was over 45% fine to medium sand (0.24-0.54 mm); they were much less abundant in areas in which substrate composition exceeded 25% particles greater than 1.9 mm. Substrate preference was tested by allowing 49 fish kept in aquaria to choose among four different substrates. The fish showed a significant preference (P &lt; 0.005) for the finer substrate categories (0.24-0.54 mm, 0.55-1.0 mm), and mostly avoided the coarser substrates (1.0-1.9 mm, 2.0-4.1 mm). This suggests that the Eastern Sand Darter is selective regarding substrate composition, and therefore might be affected by fluctuations or changes in substrate composition within its habitat, such as those caused by changes in flow.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.893
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.015
GPT teacher head0.214
Teacher spread0.200 · 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 designNot applicable
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

Citations14
Published2008
Admission routes2
Has abstractyes

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