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Record W2117546773 · doi:10.3138/jvme.28.2.62

Outcomes Assessment of the Center for Government and Corporate Veterinary Medicine at the Virginia-Maryland Regional College of Veterinary Medicine

2001· article· en· W2117546773 on OpenAlexvenueaboutno aff
Leslie S. Black, Craig D. Thatcher, William D. Hueston

Bibliographic record

VenueJournal of Veterinary Medical Education · 2001
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Veterinary medicineMedicineWork (physics)Medical educationEngineering

Abstract

fetched live from OpenAlex

INTRODUCTION: The objective of this study was to evaluate the effectiveness and usefulness of the Virginia-Maryland Regional College of Veterinary Medicine's Center for Government and Corporate Veterinary Medicine (CGCVM or Center) as a national resource. METHODOLOGY: Questionnaires were mailed to graduates of the Virginia-Maryland Regional College of Veterinary Medicine (VMRCVM) from the classes of 1993 through 1997, as well as to graduates of other veterinary schools in the United States and Canada in the classes of 1994 through 1997 who had completed externships with the Center. Agencies and corporations that had hosted student clerkships in the 1997/1998 academic year and Deans of each veterinary school that has utilized the Center for student clerkships were also surveyed by mail. CONCLUSION: The results indicate that the Center for Government and Corporate Veterinary Medicine is a valuable national resource for veterinary students interested in public practice veterinary medicine and for veterinarians already in the work force seeking career advancement and/or career redirection.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.409
GPT teacher head0.545
Teacher spread0.136 · 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.

Study designNot applicable
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

Citations7
Published2001
Admission routes2
Has abstractyes

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