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Record W2369988895 · doi:10.1093/pch/21.4.187

Preresidency publication record and its association with publishing during paediatric residency

2016· article· en· W2369988895 on OpenAlexaffabout
Ronish Gupta, Mark L. Norris, Hilary Writer

Bibliographic record

VenuePaediatrics & Child Health · 2016
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsMedicineFamily medicinePublicationResidency trainingCertificationMEDLINECurriculumLibrary sciencePediatricsMedical educationPsychologyPolitical scienceContinuing education

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine whether an association exists between the publication of journal articles before and during paediatrics residency. METHODS: A retrospective search of PubMed was conducted for publications by all 567 Canadian paediatricians certified between 2009 and 2012, inclusive. Paediatricians were separated into groups based on the number of articles published preresidency (0 or ≥1) and during residency (0 or ≥1). The methodology was validated using a group of local paediatricians who were contacted to verify whether their publications were identified accurately. RESULTS: A total of 160 of 567 (28%) certified paediatricians had preresidency publications; of these, 93 (58%) subsequently published during their residency period. Among the remaining 407 (72%) paediatricians without preresidency publications, 129 (32%) published during residency. The association between publication before and during paediatric residency was statistically significant (OR 2.98 [95% CI 2.04 to 4.36]; P<0.001). Results from the validation analysis suggested the methodology correctly identified pre- and during residency publication status with 87% and 90% accuracy, respectively. CONCLUSION: Individuals with previous publications were more likely to publish as residents; however, 42% of individuals with pre-residency publications did not publish as residents. Residency selection committees may find these data helpful in assessing the publication potential of their applicants. In addition, this information may assist in building more targeted and individualized research curricula within residency programs.

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)0.005
metaresearch head score (Gemma)0.104
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.603
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.104
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.043
GPT teacher head0.333
Teacher spread0.290 · 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 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

Citations10
Published2016
Admission routes2
Has abstractyes

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