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Record W208079382 · doi:10.1177/070674371405900506

Research-Track Programs for Residents in Psychiatry: A Review of Literature and a Report of 3 Canadian Experiences

2014· review· en· W208079382 on OpenAlexafffundvenueabout
Venkat Bhat, Jonathan Lee, Daphne Voineskos, Zafiris J. Daskalakis, Raymond W. Lam, Fabrice Jollant

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2014
Typereview
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsUniversity of TorontoUniversity of British ColumbiaMcGill University
FundersCanadian Institutes of Health Research
KeywordsPsychiatryMEDLINEPsychologyTrack (disk drive)MedicineGerontologyFamily medicineMedical educationPolitical scienceComputer science

Abstract

fetched live from OpenAlex

OBJECTIVES: Clinician-scientists occupy an interesting position at the interface between science and care, and have a role to play in bridging the 2 valleys between fundamental and clinical research, and between clinical research and clinical practice. However, research training during medical residency for future clinician scientists is an important but challenging process. Our article, written by residents and directors of research-track (RT) programs, aimed at reviewing literature on RT programs for residents, and describing the organization of RT programs at 3 Canadian universities (the University of British Columbia, the University of Toronto, and McGill University). METHODS: A systematic MEDLINE search was conducted for the review section. Psychiatry program directors in Canada were also contacted to provide information about potential RT programs. RESULTS: Twenty articles were related to resident RT programs in medicine, including 6 in psychiatry. Moreover, 5 out of 16 Canadian programs were found to offer a formal RT program, of which 3 are described here. Most reviewed articles described the program organization, while only one provided an outcome assessment with evidence of increased scholarly activity following RT implementation. CONCLUSIONS: Our article sheds light on postgraduate programs aiming at facilitating the dual training of future clinician-scientists, and developed during the last 10 years. It also highlights the lack of outcome assessment, and the paucity of guidelines to organize these programs in relation to the national requirements.

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)0.015
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.671
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.188
GPT teacher head0.500
Teacher spread0.313 · 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
GenreReview

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

Citations13
Published2014
Admission routes4
Has abstractyes

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