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Record W2612610785 · doi:10.1139/cjas-2016-0215

An observational study of naturally occurring gastrointestinal nematode infections in a seasonal grazing cow-calf herd in southern Ontario

2017· article· en· W2612610785 on OpenAlexafffundvenueabout
Kaley G Mackie, Paula M Menzies, K G Bateman, Jessica Gordon

Bibliographic record

VenueCanadian Journal of Animal Science · 2017
Typearticle
Languageen
FieldVeterinary
TopicHelminth infection and control
Canadian institutionsUniversity of Guelph
FundersAgricultural Adaptation CouncilBeef Farmers of OntarioUniversity of Guelph
KeywordsCow-calfHerdAnimal sciencePastureBiologyGrazingFecesEggs per gramIce calvingCrossbreedWeaningVeterinary medicinePregnancyMedicineLactationAgronomyEcology

Abstract

fetched live from OpenAlex

Little work has been done to determine the prevalence of gastrointestinal nematodes (GIN) in Ontario cow–calf herds. A prospective single cohort study was conducted during the grazing seasons of 2014 and 2015. Twenty-four crossbred cows were randomly assigned to one of six rotationally grazed fields each year, blocked by calving date and parity (n = 48). Feces were collected and weight and body condition score (cows) recorded at approximately 28 d intervals. Fecal egg counts (FEC) were performed using the Wisconsin method. No clinical signs of GIN parasitism were observed. Cow FEC stayed relatively low throughout both pasture seasons [mean 8 ± 20.02 eggs per gram (epg) of feces, n = 301]. Most calf FEC were also low throughout both seasons (mean 42 ± 86.20 epg, n = 268). The sample time [a proxy for days on pasture (DOP)] had a significant effect on cow epg (P < 0.001) and calf epg (P < 0.001). Cow and calf FEC peaked at the fourth sample, after 55–72 DOP; 4 epg (95% CI 2.57, 6.32) and 24 epg (95% CI 15.82, 37.19) for cows and calves, respectively. Mean calf FEC did not have a significant effect on calf weaning weight (P = 0.9).

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)0.001
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 score0.593
Threshold uncertainty score0.657

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.147
GPT teacher head0.368
Teacher spread0.221 · 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

Citations0
Published2017
Admission routes4
Has abstractyes

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