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Record W4280633455 · doi:10.1016/j.xjon.2022.04.047

The utilization of educational resources published by the Thoracic Surgery Residents Association

2022· article· en· W4280633455 on OpenAlexaff
Alexander A. Brescia, Clauden Louis, Jessica G.Y. Luc, Garrett N. Coyan, Jason J. Han, David Blitzer, Fatima G. Wilder, Curtis S. Bergquist, Jordan P. Bloom, Rishindra M. Reddy, Gurjit Sandhu, J. Hunter Mehaffey

Bibliographic record

VenueJTCVS Open · 2022
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCardiothoracic surgeryMedicineCertificationBoard certificationResidency trainingMedical educationEducational resourcesFamily medicineGeneral surgerySurgeryPsychologyContinuing educationManagementPedagogy

Abstract

fetched live from OpenAlex

Objective: The Thoracic Surgery Residents Association (TSRA) is a trainee-led cardiothoracic surgery organization in North America that has published a multitude of educational resources. However, the utilization of these resources remains unknown. Methods: Surveys were constructed, pilot-tested, and emailed to 527 current cardiothoracic trainees (12 questions) and 780 former trainees who graduated between 2012 and 2019 (16 questions). The surveys assessed the utilization of TSRA educational resources in preparing for clinical practice as well as in-training and American Board of Thoracic Surgery (ABTS) certification examinations. Results: < .001). Conclusions: Current cardiothoracic trainees and recent graduates have utilized TSRA educational resources extensively, including to prepare for in-training and ABTS Board examinations.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.379
Teacher spread0.309 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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