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d-Lactate Production and Excretion in Diarrheic Calves

2004· article· en· W2030095137 on OpenAlexaff
Julia B. Ewaschuk, Jonathan Μ. Naylor, Randi Palmer, Susan J. Whiting, Gordon A. Zello

Bibliographic record

VenueJournal of Veterinary Internal Medicine · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsRumenUrineFecesAnion gapAcidosisExcretionMedicineAnimal scienceBicarbonateInternal medicineMetabolic acidosisEndocrinologyFermentationBiologyBiochemistryMicrobiology

Abstract

fetched live from OpenAlex

The origin of D-lactate, the most important acid contributing to metabolic acidosis in the diarrheic calf, is unknown. We hypothesized that because D-lactate is produced only by microbes, gastrointestinal fermentation is the source. The objective of this study was to determine whether D-lactate production occurs in the rumen, colon, or both, and to measure D- and L-lactate concentrations in urine. Fecal, rumen, blood, and urine samples were obtained from 16 diarrheic and 11 healthy calves. Serum electrolyte concentrations were measured in both groups, and blood gas analyses were performed for diarrheic calves. All samples were analyzed for D- and L-lactate by high performance liquid chromatography (HPLC). Diarrheic calves were generally hyperkalemic with high serum anion gap, depressed serum bicarbonate, and low blood pH. L-lactate was markedly higher in rumen contents (22.7 mmol/ L [median]) and feces (8.6 mmol/L) of diarrheic calves than healthy calves (0.5 mmol/L and 5.1 mmol/L, respectively), but not different in serum or urine. Rumen, fecal, serum, and urine D-lactate concentrations were all significantly higher (P < .05) in diarrheic calves (17.0, 25.4, 13.9, and 19.2 mmol/L, respectively) than in healthy calves (0.5, 9.1, 1.4, and 0.5 mmol/L, respectively). Higher D-lactate concentrations in the rumen and feces of diarrheic calves suggests these sites as the source of D-lactate in blood and urine.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.978
Threshold uncertainty score0.099

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.034
GPT teacher head0.284
Teacher spread0.249 · 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 designBench or experimental
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

Citations69
Published2004
Admission routes1
Has abstractyes

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