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Record W7010567874

INCREASING OF THE POSSIBILITIES OF THE CLINICAL BOVINE PATHOLOGY SOFTWARE SIMUL : CREATION OF 10 NEW CLINICAL CASES

2001· other· fr· W7010567874 on OpenAlexaboutno aff

Bibliographic record

VenueOpenGrey (Institut de l'Information Scientifique et Technique) · 2001
Typeother
Languagefr
FieldVeterinary
TopicInfectious Diseases and Mycology
Canadian institutionsnot available
Fundersnot available
KeywordsSoftwareMEDLINEComputer softwareSoftware tool
DOInot available

Abstract

fetched live from OpenAlex

L'auteur a augmenté le nombre de cas portés par le didacticiel SIMUL, logiciel de d'enseignement clinique vétérinaire en médecine bovine, développé par le professeur Denis Harvey de la faculté vétérinaire d e Montréal. Cette extension comprend 10 nouveaux cas de pathologie bovine, destinés à être utilisés par les étudiants vétérinaires. L'auteur les a voulu pratiques, c'est-à-dire qu'il les a lui-même rencontrés au cours de son récent exercice en milieu rural. Cette partie logicielle est accompagnée d'un petit fascicule composant la partie écrite de cette thèse et qui élargit l'analyse de chaque cas présenté.

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)0.009
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Software · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0160.005

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 head0.050
GPT teacher head0.364
Teacher spread0.314 · 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 designSimulation or modeling
Domainnot available
GenreSoftware

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
Published2001
Admission routes1
Has abstractyes

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