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Record W6957843816 · doi:10.60692/hfers-x3816

Development of an International Standard Set of Outcomes and Measurement Methods for Routine Practice for Infants, Children, and Adolescents with Epilepsy: The International Consortium for Health Outcomes Measurement Consensus Recommendations

2024· article· en· W6957843816 on OpenAlexaff

Bibliographic record

VenueGreater South Information System · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDelphi methodSet (abstract data type)DelphiOutcome (game theory)MEDLINEInternational standardVotingCore (optical fiber)

Abstract

fetched live from OpenAlex

Abstract At present, there is no internationally accepted set of core outcomes or measurement methods for epilepsy clinical practice. The International Consortium for Health Outcomes Measurement (ICHOM) convened an international working group of experts in epilepsy, people with epilepsy, and their representatives to develop minimum sets of standardized outcomes and outcome measurement methods for clinical practice. Using modified Delphi consensus methods with consecutive rounds of online voting over 12 months, a core set of outcomes and corresponding measurement tool packages to capture the outcomes were identified for infants, children, and adolescents with epilepsy. Consensus methods identified 20 core outcomes. In addition to the outcomes identified for the ICHOM Epilepsy adult standard set, behavioral, motor, and cognitive/language development outcomes were voted as essential for all infants and children with epilepsy. The proposed set of outcomes and measurement methods will facilitate the implementation of the use of patient‐centered outcomes in daily practice.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.522
metaresearch head score (Gemma)0.517
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.478
Threshold uncertainty score0.589

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.5220.517
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0050.009
Bibliometrics0.0130.008
Science and technology studies0.0040.003
Scholarly communication0.0090.007
Open science0.0090.012
Research integrity0.0050.014
Insufficient payload (model declined to judge)0.0030.002

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 head0.064
GPT teacher head0.337
Teacher spread0.274 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designTheoretical or conceptual
DomainReporting
GenreMethods

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

Citations0
Published2024
Admission routes1
Has abstractyes

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