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Impact of Lowering Dietary Cation-Anion Difference in Nonlactating Dairy Cows: A Meta-Analysis

2006· review· en· W2108860438 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.

Bibliographic record

VenueJournal of Dairy Science · 2006
Typereview
Languageen
FieldVeterinary
TopicAnimal health and immunology
Canadian institutionsUniversité Laval
FundersFonds Québécois de la Recherche sur la Nature et les TechnologiesNovalaitMinistère de l'Agriculture, des Pêcheries et de l'AlimentationUniversity of Wisconsin-Madison
KeywordsMilk feverChemistryAnimal scienceUrineIce calvingUrinary systemRespiratory compensationBicarbonateAcidosisMetabolic acidosisInternal medicineEndocrinologyMedicineLactationPhysiologyPregnancyBiochemistryAnaerobic exerciseBiology

Abstract

fetched live from OpenAlex

A meta-analysis of previous studies was performed to clarify the response of prepartum dairy cows to lowering dietary cation-anion difference (DCAD) and to compare different equations that have been proposed to calculate DCAD. Twenty-two published studies containing 75 treatment groups met criteria for inclusion in the meta-analysis. Five different equations used to calculate DCAD were compared for their association with clinical milk fever and urinary pH. The DCAD equation (Na + K) - (Cl + 0.6 S) was the most highly associated with clinical milk fever (R(2) = 0.44) and urinary pH (R(2) = 0.85). Lowering DCAD reduced clinical milk fever but also reduced DM intake. Lowered DCAD was associated with reduced urinary pH, blood bicarbonate, and blood CO(2), suggesting a metabolic acidosis with respiratory compensation. Blood pH was very slightly lowered by lowered DCAD. Lowering DCAD increased ionized Ca in blood before and at calving. The model predicted that lowering DCAD from +300 to 0 mEq/kg reduced risk for clinical milk fever from 16.4 to 3.2%, reduced urinary pH from about 8.1 to 7.0, and reduced DM intake by 11.3%.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.879
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0020.003
Science and technology studies0.0000.000
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 head0.226
GPT teacher head0.460
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