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Record W2123803566 · doi:10.3138/jvme.33.4.605

Survey of the Large-Animal Diplomates of the American College of Veterinary Internal Medicine Regarding Knowledge and Clinical Use of Polymerase Chain Reaction: Implications for Veterinary Education

2006· article· en· W2123803566 on OpenAlexvenueno aff
Nicola Pusterla, S. Mapes, Christian M. Leutenegger

Bibliographic record

VenueJournal of Veterinary Medical Education · 2006
Typearticle
Languageen
FieldVeterinary
TopicVeterinary medicine and infectious diseases
Canadian institutionsnot available
Fundersnot available
KeywordsVeterinary medicineMedicinePolymerase chain reactionContinuing educationBiologyMedical education

Abstract

fetched live from OpenAlex

A questionnaire was developed to document the knowledge base of large-animal diplomates of the American College of Veterinary Internal Medicine (ACVIM) regarding polymerase chain reaction (PCR) technology and to identify the common use of this technology in equine practice. Ninety-three of the 278 mailed questionnaires were returned, for an overall response rate of 33.4%. Ninety respondents (99%) reported being familiar with the general principles of nucleic acid probe technology; however, only 52 (57%) knew the difference between conventional (traditional) and real-time (second-generation) PCR. The majority of the respondents (88%) emphasized the need for continuing education on molecular diagnostics. Eighty-four (92%) of the respondents regularly use PCR (conventional and/or real-time) for the detection of equine pathogens, and 80 (88%) commonly submit their samples to university/state veterinary laboratories. Blood, nasal swabs, and feces are the three equine specimens most commonly submitted for PCR analysis of Streptococcus equi, Lawsonia intracellularis, Neorickettsia risticii, equine herpesvirus 1/4, Rhodococcus equi, Sarcocystis neurona, and equine influenza virus. Diplomates reported costs associated with molecular diagnostics and unreliability of PCR as the most common limitations of PCR. Didactic training in veterinary curricula and during continuing-education opportunities continues to be necessary to produce veterinarians who have an understanding of the clinical applications of molecular diagnostics.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.358
Threshold uncertainty score0.821

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.137
GPT teacher head0.454
Teacher spread0.317 · 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 designObservational
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

Citations4
Published2006
Admission routes1
Has abstractyes

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