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Record W4225324579

[Observing a resident doing a consultation with a patient: goal determines form].

2022· article· en· W4225324579 on OpenAlexaff
Paul L.P. Brand, Nynke Scherpbier

Bibliographic record

VenuePubMed · 2022
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsBrandon University
Fundersnot available
KeywordsSupervisorMedicineContext (archaeology)Task (project management)Medical educationCitizen journalismNursingApplied psychologyPsychologyComputer scienceManagement
DOInot available

Abstract

fetched live from OpenAlex

Observation of residents by supervisors is a highly recommended, but underused educational tool in postgraduate medical education. Observation can be performed indirectly (using video recordings of residents performing clinical tasks) or directly (supervisor is present when the resident performs the task). The choice of the observation method depends on aim and context of the observation. In general practice, patients tend to involve the supervisor when the resident performs the consultation. They value such participatory direct observation because they know the supervisor and appreciate their input. For specific residents' learning aims (e.g. consultation efficiency), it may be more useful if the supervisor takes a "fly on the wall" approach. Supervisors wishing to take a "fly on the wall" approach to direct observation need to inform the patient about their role and position themselves outside the patient's field of view. Indirect observation by reviewing video-recorded consultations is an alternative for this purpose.

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)0.008
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.028
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0200.013

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 head0.014
GPT teacher head0.244
Teacher spread0.230 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2022
Admission routes1
Has abstractyes

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