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Record W1440382967 · doi:10.21423/aabppro20074624

Impact of Milk Temperature Monitoring on Milk Quality on Ontario Dairy Farms

2007· article· en· W1440382967 on OpenAlexaffabout
Nathan Perkins, D.F. Kelton, K. Leslie, Karen J. Hand, G. MacNaughton

Bibliographic record

VenueAmerican Association of Bovine Practitioners Conference Proceedings · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Supply Chain Traceability
Canadian institutionsDairy Farmers of OntarioUniversity of Guelph
Fundersnot available
KeywordsRaw milkPasteurizationBulk tankEnvironmental scienceContaminationDairy industryAgricultural scienceFood scienceRaw materialAgricultureBusinessAnimal scienceGeographyBiologyHerd

Abstract

fetched live from OpenAlex

The Ontario dairy industry takes great pride in providing high quality milk products to the consuming public. Milk and milk products are an important part of the daily diet of most Ontario residents. Bacterial contamination of raw milk has a major negative impact on milk quality. Even though most milk is pasteurized prior to consumption, raw milk is consumed by some farming families and is used to manufacture some food products. Dairy Farmers of Ontario have required installation of Time Temperature Recorder's (TTR's) on all Ontario dairy farms, with the intention of preventing elevated bacteria levels in raw milk under the Canadian Quality Milk Program. The TTR has two sensors, one in the bulk tank that monitors the raw milk temperature and one in the pipeline to monitor wash water temperature during the wash cycle. The objective of this study was to evaluate the impact of TTR's on the bacterial content of raw milk and the loss of (dumped) bulk tank milk on Ontario dairy farms and to summarize the occurrences of the different TTR alarms.

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 score0.207
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.024
GPT teacher head0.296
Teacher spread0.272 · 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
Published2007
Admission routes2
Has abstractyes

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Same venueAmerican Association of Bovine Practitioners Conference ProceedingsSame topicFood Supply Chain TraceabilityFrench-language works237,207