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Record W1935149836 · doi:10.1186/cc3383

The reliability of electrocardiogram interpretation in critically ill patients

2005· article· en· W1935149836 on OpenAlexaff
Wendy Lim, Ismael Qushmaq, A Tkacyzk, Laura Donahoe, Diane Heels‐Ansdell, J. Hancock, Ellen McDonald, Mark Crowther, P.J. Devereaux, Richard J. Cook, DJ Cook

Bibliographic record

VenueCritical Care · 2005
Typearticle
Languageen
FieldMedicine
TopicECG Monitoring and Analysis
Canadian institutionsUniversity of WaterlooMcMaster University
FundersNational Institutes of Health
KeywordsMedicineFamily medicine

Abstract

fetched live from OpenAlex

Critically ill patients are generally unable to report ischemic chest pain due to decreased consciousness, endotracheal intubation, and use of sedatives and narcotics. The diagnosis of cardiac ischemia is therefore usually based on elevated cardiac enzymes and typical ischemic changes on an electrocardiogram (ECG). Although key management decisions depend on ECG interpretation, the reproducibility of ECG interpretation is unclear in the ICU. To estimate the inter-rater and intra-rater reliability of ECG interpretation for the presence of myocardial ischemia in critically ill patients, with and without knowledge of troponin T values.

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)0.000
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.265
Threshold uncertainty score0.882

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.007
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 head0.006
GPT teacher head0.308
Teacher spread0.301 · 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 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

Citations1
Published2005
Admission routes1
Has abstractyes

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