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Record W1986114019 · doi:10.3138/jvme.34.4.485

The ECVP/ESVP Summer School in Veterinary Pathology: High-Standard, Structured Training for Young Veterinary Pathologists

2007· article· en· W1986114019 on OpenAlexvenueno aff
Anja Kipar, Mona Aleksandersen, Cinzia Benazzi, Thomas Hodge, Antti Sukura, Monique Wyers

Bibliographic record

VenueJournal of Veterinary Medical Education · 2007
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsVeterinary pathologyVeterinary medicineMedical educationMedicineWork (physics)Pathology

Abstract

fetched live from OpenAlex

This article describes the ECVP/ESVP Summer School in Veterinary Pathology, a new annual two-week European training facility established by the European College of Veterinary Pathologists (ECVP) in collaboration with the European Society of Veterinary Pathology (ESVP). The aim of the Summer Schools is to provide Europe-wide, harmonized, top-standard theoretical and practical post-graduate training for veterinarians specializing in veterinary pathology. In particular, it aims to support trainees in veterinary pathology in their individual preparation for the ECVP certifying examination. Ultimately, it aims to provide young pathologists with the skills and knowledge necessary to participate in international, high-quality research and the tools for applying international standards to their own research and for independent study for the ECVP certifying examination, even if they do not work in comparable academic environments and do not have the same level of local support and training. The ECVP/ESVP Summer Schools take place in European countries, with local organization from a university department of veterinary pathology. Each event comprises modules provided by internationally recognized specialists in their specific fields of expertise on different organ systems, diseases of specific species, specific techniques, and specific topics relevant to pathology, forming a cycle of four events to cover all major topics. Every two years a mock exam is organized as a tool to monitor individual progress in preparing for the ECVP certifying examination.

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)0.010
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.621
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.360
GPT teacher head0.548
Teacher spread0.188 · 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 designOther design
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
Published2007
Admission routes1
Has abstractyes

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