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Record W2109133699

PRODUCTION D’ANTICORPS POLYCLONAUX ANTI - PROTEINE A DE STAPHYLOCOCCUS AUREUS : OPTIMISATION D’UNE TECHNIQUE E.L.I.S.A. POUR LE CONTROLE DE QUALITE DU LAIT

2008· article· fr· W2109133699 on OpenAlexaff
Mohammed Bénali, Y Belkessam, Boumediene Khaled Meghit, Soraya Moulessehoul, Slimane Belbraouet

Bibliographic record

VenueSCIENCE & TECHNOLOGY. C, BIOTECHNOLOGY · 2008
Typearticle
Languagefr
FieldVeterinary
TopicVeterinary medicine and infectious diseases
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsAntiserumMolecular biologyPolyclonal antibodiesMedicineBiologyAntibodyImmunology
DOInot available

Abstract

fetched live from OpenAlex

L’objectif de cet article est la production d’anticorps polyclonaux dirigés contre la protéine A deS. aureus et leur utilisation pour apprécier la qualité bactériologique du lait. A cet effet, unprotocole d’immunisation est mis au point pour déceler, dans un lot d’animaux, les bonsrépondeurs à l’antigène injecté. La réalisation d’un tableau croisé nous a permis d’optimiser lesdifférentes concentrations des différents réactifs utilisés pour le test E.L.I.S.A. Les dilutions de :- 1/1000 pour l’antisérum de souris anti-pSA et 1/2000 pour l’antisérum de lapin anti-pSA,- 1/4000 pour l’antisérum de souris anti-Sc et 1/500 pour l’antisérum de lapin anti-pSA,- et 1/2000 pour le polyclonal de souris anti-Sj et 1/500 pour l’antisérum de lapin anti-pSA,ont été retenues. L’application du test E.L.I.S.A. optimisé à la recherche de S. aureus dansdifférents échantillons de lait a donné des résultats satisfaisants en comparaison avec ceuxobtenus par la méthode bactériologique. En effet la sensibilité, la reproductibilité ainsi que lapossibilité d’analyse d’un grand nombre d’échantillons à la fois en un temps réduit font de laméthode immunochimique une méthode de choix capable de remplacer les méthodesmicrobiologiques classiques actuellement utilis

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesScience and technology studies
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 score0.143
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.008
Science and technology studies0.0020.014
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0030.002
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 head0.025
GPT teacher head0.287
Teacher spread0.262 · 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; both teacher heads agree on what is shown here.

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
Published2008
Admission routes1
Has abstractyes

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