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Record W1993266773 · doi:10.1139/f03-004

Cyprinid fishes as samplers of benthic diatom communities in freshwater streams of varying water quality

2003· article· en· W1993266773 on OpenAlexvenueno aff
Ted C Rosati, Jeffrey R. Johansen, Miles M. Coburn

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2003
Typearticle
Languageen
FieldMaterials Science
TopicDiatoms and Algae Research
Canadian institutionsnot available
FundersJohn Carroll University
KeywordsDiatomSTREAMSBenthic zoneWater qualityBiologyMinnowFish <Actinopterygii>CyprinidaeEcologyFisheryEnvironmental science

Abstract

fetched live from OpenAlex

The diatom composition of natural substrates in streams of different water qualities was compared among samples collected by researchers and samples collected from the intestine contents of three species of Cyprinid fishes: Campostoma anomalum, Pimephales notatus, and Semotilus atromaculatus. Campostoma and Pimephales were found to be robust samplers that efficiently collected diverse, representative diatom samples. Semotilus were adequate diatom samplers but collected the most diverse samples. In no instance were water-quality indices calculated from Pimephales samples significantly different from human-collected composite samples, whereas Campostoma and Semotilus samples diverged slightly from human-collected composite samples. Internal similarities of fish-collected samples were not significantly higher than those of human-collected samples, indicating that the fish were indiscriminately foraging on diatoms. Furthermore, samples clustered primarily by stream, indicating that fish-collected samples of diatoms were as representative of the stream as those collected by human researchers. By all standards measured in this study, these three fish species sample the benthic diatom community of mid-order streams with a facility equal to that of trained ecologists.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.057
GPT teacher head0.291
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations15
Published2003
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Fisheries and Aquatic SciencesSame topicDiatoms and Algae ResearchFrench-language works237,207