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Record W2556849768 · doi:10.1186/s13104-016-2290-1

The psychiatry resident research experience

2016· article· en· W2556849768 on OpenAlexafffundabout
Frank P. MacMaster, Jordan Cohen, Waqar Waheed, Emilie Magaud, Mariko Sembo, Lisa Marie Langevin, Katherine Rittenbach

Bibliographic record

VenueBMC Research Notes · 2016
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsAlberta Health ServicesAlberta Children's HospitalAlberta HealthUniversity of Calgary
FundersHotchkiss Brain Institute, University of Calgary
KeywordsPracticumMedicineCurriculumMedical educationFamily medicinePsychiatryPsychologyPedagogy

Abstract

fetched live from OpenAlex

BACKGROUND: Research activity is especially critical in the field of psychiatry as it is evolving rapidly thanks to advances in neuroscience. RESULTS: We administered a 34-item survey regarding research experiences targeted at psychiatry residents and postgraduate residency program directors in Canada. One hundred and nineteen participants answered the survey (16 program directors, 103 residents) allowing for a margin of error of 8.4% at a 95% confidence interval. Research was rated as important in informing clinical practice (87.0% yes, 13.0% no), but only 28.7% of respondents reported that it was taught well at their home institution (33.0% no, 38.3% neutral). Only a small proportion was enthusiastic or very enthusiastic about participating in research (21.7%). CONCLUSIONS: While the importance of research is recognized, there is little consensus with respect to whether a standardized research practicum component is included in the resident curriculum.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.989
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.697
GPT teacher head0.643
Teacher spread0.054 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
DomainIncentives
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
Published2016
Admission routes3
Has abstractyes

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