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Record W2390041301 · doi:10.1093/pch/21.4.e32

Patient disclosure of medical errors in paediatrics: A systematic literature review

2016· review· en· W2390041301 on OpenAlex
Donna Koller, Anneke Rummens, Morgane Le Pouesard, Sherry Espin, Jeremy Friedman, Maitreya Coffey, Noah Kenneally

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePaediatrics & Child Health · 2016
Typereview
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMedicinePediatrics

Abstract

fetched live from OpenAlex

Medical errors are common within paediatrics; however, little research has examined the process of disclosing medical errors in paediatric settings. The present systematic review of current research and policy initiatives examined evidence regarding the disclosure of medical errors involving paediatric patients. Peer-reviewed research from a range of scientific journals from the past 10 years is presented, and an overview of Canadian and international policies regarding disclosure in paediatric settings are provided. The purpose of the present review was to scope the existing literature and policy, and to synthesize findings into an integrated and accessible report. Future research priorities and policy implications are then identified.

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.

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)0.018
metaresearch head score (Gemma)0.033
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.461
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0090.001
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0010.001

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 head0.045
GPT teacher head0.436
Teacher spread0.392 · 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