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Variation in Infections of<i>Myxobolus cerebralis</i>in Field-Exposed Cutthroat and Rainbow Trout in Idaho

2001· article· en· W2047960124 on OpenAlexaboutno aff
M.M. Hiner, Christine M. Moffitt

Bibliographic record

VenueJournal of Aquatic Animal Health · 2001
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMyxozoan Parasites in Aquatic Species
Canadian institutionsnot available
Fundersnot available
KeywordsRainbow troutTroutBiologyMyxobolusOncorhynchusHistologyVeterinary medicineZoologyFish <Actinopterygii>EcologyFisheryMedicine

Abstract

fetched live from OpenAlex

We evaluated the severity and extent of infection by Myxobolus cerebralis in replicated groups of same-age Yellowstone cutthroat trout Oncorhynchus clarki bouvieri and Kamloops rainbow trout O. mykiss exposed to natural river conditions at four sites along a 25-km reach of the South Fork of the Boise River. Groups of fry were each exposed for 10 d in June, July, or August and then removed from the river and reared in specific-pathogen-free water under controlled laboratory conditions for 84 d. At the end of the study, surviving fish were examined for clinical signs of disease, and fish heads were evaluated by histology for the presence of characteristic pathology and then scored for the extent of pathology on a five-point scale. The mean histological scores and percent of fish testing positive in both species were similar within each site but varied across the study sites from no infection in fish at the uppermost site to 90–100% testing positive at the lowermost site. Cutthroat trout with moderate histology scores had significantly higher prevalence of exophthalmia and cranial deformities than did similarly infected rainbow trout. Habitat characteristics such as water temperature and the combined mean abundance of oligochaetes and chironomids were significantly different among the study sites and were positively correlated with the disease severity detected by histology.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.434

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 studies0.0000.000
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 head0.015
GPT teacher head0.304
Teacher spread0.289 · 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.

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

Citations30
Published2001
Admission routes1
Has abstractyes

Explore more

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