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Record W4407571608 · doi:10.1002/aet2.70000

The standardized letter of evaluation (SLOE) in emergency medicine: The internal validity of the SLOE 2.0

2025· article· en· W4407571608 on OpenAlexaff
Alexandra Mannix, Cullen Hegarty, Sharon Bord, Thomas Beardsley, Sandra Monteiro, Al’ai Alvarez, Teresa Davis, Katarzyna Gore, Melissa Parsons, Aman Pandey, Sara Krzyzaniak, Michael Gottlieb

Bibliographic record

VenueAEM Education and Training · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSpearman's rank correlation coefficientRank correlationDescriptive statisticsRanking (information retrieval)CorrelationMedicineStatisticsPsychologyFamily medicineMathematicsComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Background: The standardized letter of evaluation (SLOE) is a crucial component of emergency medicine (EM) residency applications. Initially developed in 1995 and revised to electronic SLOE (eSLOE) 2.0, this tool aims to provide a standardized evaluation of medical students. Objective: This study aimed to conduct internal validation by analyzing the distribution and correlation of scores in eSLOE 2.0 and identify any ranking skew. Methods: A multi-institutional cross-sectional study conducted using eSLOE 2.0 data from applicants to five geographically diverse U.S. EM residency programs during the 2022-2023 application cycle. Data from 2891 eSLOE 2.0 s across 1633 applicants were analyzed using descriptive statistics, chi-square, and Spearman's rho. Results: Scores for all questions were moderately left-skewed. The mean scores for all part B questions were above 4.0. Strong correlations were found between part A and B scores with anticipated guidance (AG) and rank list (RL) positions. The AG had a higher correlation with RL positions than grades. The mean RL score indicated that the average student fell between the middle and top thirds. Conclusions: The study demonstrates left skew in eSLOE 2.0 scoring, including a higher prevalence of scores in the fully and mostly entrustable ranges for part A and the consistently high scores in part B.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score0.230

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.078
GPT teacher head0.404
Teacher spread0.327 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2025
Admission routes1
Has abstractyes

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