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Record W3138694578 · doi:10.21423/aabppro20123939

Evaluation of serum immunoglobulin G concentrations in dairy calves by use of an automated turbidimetric immunoassay

2012· article· en· W3138694578 on OpenAlexaff
M.L. Alley, Deborah M. Haines, Geoffrey Smith

Bibliographic record

VenueAmerican Association of Bovine Practitioners Conference Proceedings · 2012
Typearticle
Languageen
FieldVeterinary
TopicAnimal health and immunology
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsColostrumImmunoassayPassive immunityDairy cattleAntibodyImmunoglobulin GMedicineImmunologyImmunityAnimal scienceImmune systemBiology

Abstract

fetched live from OpenAlex

Administration of colostrum to newborn calves is recognized as an important component of dairy calf health maintenance because colostral immunoglobulin absorption is required to establish passive immunity. Despite the importance of a good colostrum management program, over one-third of dairy operations still depend on the calf nursing the dam as the only method for colostrum delivery, and 19.2% of calves are estimated to have failure of transfer of passive immunity. Multiple assays have been described to assess serum immunoglobulin G (lgG) concentrations in calves; however, none are ideal for routine use on farms. The purpose of this study was to evaluate the reliability of a new commercially available automated turbidimetric immunoassay and portable analyzer for measuring serum IgG concentrations in dairy calves.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.068
GPT teacher head0.374
Teacher spread0.306 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2012
Admission routes1
Has abstractyes

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