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<b>Diferentes pontos de vista na avaliação do médico residente em programas de clínica médica/ Different points of view in the evaluation of the resident physician in medical clinic programs<b>

2019· article· pt· W2915976989 on OpenAlexaff
Luiz Carlos Toso, Juliano Mendes de Souza, Elaine Rossi Ribeiro

Bibliographic record

VenueCiência Cuidado e Saúde · 2019
Typearticle
Languagept
FieldHealth Professions
TopicHealth, Nursing, Elderly Care
Canadian institutionsInstitute for Clinical Evaluative Sciences
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Introdução: Este estudo enfoca a avaliação do médico residente em seu processo de formação profissional. Objetivo: compreender o processo de avaliação do médico residente em programas de clínica médica, sob o olhar dos distintos atores. Métodos: Pesquisa qualitativa, descritiva, desenvolvida em dois programas de residência em clínica médica, com os coordenadores dos dois programas, oito preceptores e15 médicos residentes, totalizando 21 participantes. Coleta de dados com grupo focal e entrevistas gravadas, analisadas por meio de análise de conteúdo, em duas categorias temáticas. Apresenta-se nesse artigo o tema “a avaliação do médico residente sob os pontos de vista dos diferentes atores envolvidos no processo de avaliação”. Resultados: Encontrou-se disparidade na percepção da avaliação entre os diferentes atores, subjetividade na avaliação, inexistência de regras claras e de conhecimento de todos, remetendo a fragilidade no processo avaliativo. Considerações Finais: Recomenda-se adotar na formação em residência médica, estratégias de avaliação estruturadas e que permitam aos envolvidos conhecer o processo avaliativo.

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)0.028
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.327
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0280.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.070
GPT teacher head0.413
Teacher spread0.343 · 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; both teacher heads agree on what is shown here.

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

Citations2
Published2019
Admission routes1
Has abstractyes

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