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Record W2220415958 · doi:10.18192/uojm.v4i1.1035

The Clinician Investigator Program at the University of Ottawa

2014· article· en· W2220415958 on OpenAlexvenueaboutno aff
Jonathan B. Angel

Bibliographic record

VenueUniversity of Ottawa Journal of Medicine · 2014
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineFamily medicineMedical educationMedical school

Abstract

fetched live from OpenAlex

ABSTRACTClinician investigators play a critical role in developing new approaches and improving upon existing approaches to medical care, ultimately resulting in improved health of Canadians. Such individuals are uniquely suited to conduct research that addresses clinical observations as well as translates research findings into novel approaches to disease management and prevention. The need for such individuals has long been recognized and in 1995, the Royal College of Physician and Surgeons of Canada (RCPSC) developed the first formal training program in the country to help support the development of clinician investigators. Since its inception, over 200 trainees have completed the RCPSC Clinician Investigator Program (CIP), the details of which are communicated in a review by Cathy Hayward et al. [1] in Clinical and Investigative Medicine. Currently, the CIP is active at 15 (almost all) medical schools across the country. Dr. Andrew Badley, a clinician scientist in the Division of Infectious Disease, led the development of the application for the CIP at the University of Ottawa (U of O), which was ultimately approved in 2002. In 2003 Jonathan Angel became the Director of the CIP at U of O and in 2004, the first trainee was accepted into the program. Since then, approximately 40 trainees have enrolled in the CIP, and as of April 2014, 25 trainees have completed the program. While a few of the recent trainees have resumed clinical training following their research activities, the majority of the graduates (n=14) have gone on to assume academic positions at the University of Ottawa and elsewhere.RÉSUMÉ Les cliniciens-chercheurs jouent un rôle clé dans le développement de nouvelles méthodes et dans l’amélioration des méthodes existantes dans les soins médicaux. Le but est, ultimement, d’améliorer la santé des Canadiens et Canadiennes. Ces personnes sont bien placées pour mener des projets de recherche qui portent sur des observations cliniques et qui traduisent les résultats de recherche en approches novatrices pour la prévention et la prise en charge des maladies. Le besoin pour ces professionnels est reconnu depuis longtemps. En 1995, le Collège royal des médecins et chirurgiens du Canada (CRMCC) a créé le premier programme officiel pour appuyer le perfectionnement des cliniciens-chercheurs. Depuis sa création, plus de 200 personnes ont complété le Programme de cliniciens-chercheurs (PCC) du CRMCC. Une revue du programme a été publiée par Cathy Hayward et coll., dans la revue Clinical and Investigative Medicine. Actuellement, le PCC est offert dans 15 facultés de médecine au Canada, soit presque la totalité d’entre elles. Dr Andrew Badley, un clinicien-scientifique de la Division des maladies infectieuses, a mené l’intégration du PCC à l’Université d’Ottawa, programme qui a été approuvé ultimement en 2002. En 2003, Jonathan Angel est devenu le directeur du PCC de l’Université d’Ottawa et, en 2004, le premier stagiaire du programme était admis. Depuis cette date, environ 40 stagiaires se sont inscrits au PCC et, en avril 2014, 25 d’entre eux avaient terminé le programme. Bien que quelques-uns des plus récents stagiaires aient repris leur formation clinique après avoir achevé leur recherche, la majorité des finissants (n=14) ont accepté des fonctions universitaires à l’Université d’Ottawa ou ailleurs.

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)0.006
metaresearch head score (Gemma)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.420
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.064
GPT teacher head0.350
Teacher spread0.286 · 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

Citations0
Published2014
Admission routes2
Has abstractyes

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