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Record W3085552426 · doi:10.3168/jds.2020-18907

Technical note: Is fecal consistency scoring an accurate measure of fecal dry matter in dairy calves?

2020· article· en· W3085552426 on OpenAlex

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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Dairy Science · 2020
Typearticle
Languageen
FieldVeterinary
TopicAnimal health and immunology
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaBayer Animal HealthDairy Farmers of Manitoba
KeywordsFecesAnimal scienceDry matterConsistency (knowledge bases)MedicineMathematicsVeterinary medicineBiologyEcology

Abstract

fetched live from OpenAlex

The objective of this cross-sectional study was to evaluate the accuracy of fecal consistency scoring as a measure of fecal dry matter (DM) in dairy calves. This study was conducted at a commercial grain-fed veal facility in southwestern Ontario. A total of 160 calves arrived at the facility in 2 groups of 80 calves each. Calves were fed milk replacer twice daily at 0700 and 1700 h and had ad libitum access from arrival onward to water through nipple drinkers and starter through a shared trough. Fecal consistency scores were evaluated once daily in the first 28 d after arrival before milk feeding. The fecal consistency scoring was conducted using a 4-level scoring scale: 0 = normal (firm but not hard); 1 = soft (does not hold form, piles but spreads slightly); 2 = runny (spreads readily); and 3 = watery (liquid consistency, splatters). Fecal samples were collected from all calves via rectal palpation on d 1, 7, 14, and 21 at 0900 h for determination of fecal DM. Mixed repeated measures linear regression models were built to assess the accuracy of fecal consistency scoring in predicting fecal DM. Over 4 selected time points (d 1, 7, 14, and 21) the 160 calves were observed, 382 (61.6%) had a fecal consistency score of 0, 121 (19.5%) had a score of 1, 85 (13.7%) had a score of 2, and 32 (5.2%) had a score of 3. A fecal score of 0 had a fecal DM of 25.1 ± 8.4%, whereas a fecal score of 1 had a DM of 21.8 ± 8.2%. With respect to calves that had a fecal score of 2 or 3, their fecal DM was 16.0 ± 11.1% and 10.7 ± 6.9%, respectively. In evaluating the pairwise comparisons generated in the repeated measures model that controlled for day of sampling, a fecal score of 0 had a 3.2%, 8.1%, and 12.0% higher fecal DM, respectively, when compared with those that had a fecal score of 1, 2, and 3. In addition, calves with a fecal score of 1 had a 5.0% and 8.8% higher fecal DM than calves with a fecal score of 2 and 3, respectively. Finally, calves with a fecal score of 2 had a 3.8% higher fecal DM than those with a fecal score of 3. This study confirms that using observational fecal consistency scoring can accurately predict diarrhea or a decline in fecal DM.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.779
Threshold uncertainty score0.538

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.103
GPT teacher head0.376
Teacher spread0.273 · 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