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Updates and Improvements to the American Academy of Neurology Guideline Dissemination Practices (P15-7.002)

2022· article· en· W4389368485 on OpenAlexaff
Sarah Tanveer, Sonja Potrebic, Mark R. Keezer, Navdeep Sangha, Vishwanath Sagi, Scott Heller, Mia T. Minen, Anne Constantino, Mark S. Johnson, Benzi M. Kluger, Kelly L. Sullivan, Scott R. Wessels

Bibliographic record

VenueNeurology · 2022
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsGuidelineNeurologyMedicineMedical educationFamily medicineMedical physicsPsychiatryPathology

Abstract

fetched live from OpenAlex

To detail the process taken to review and update guideline dissemination practices by the American Academy of Neurology (AAN) Clinical Practice Guideline Subcommittee Dissemination workgroup.

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)0.063
metaresearch head score (Gemma)0.250
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.937
Threshold uncertainty score0.332

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0630.250
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0070.005
Science and technology studies0.0020.001
Scholarly communication0.0070.005
Open science0.0040.005
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0520.041

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 head0.112
GPT teacher head0.505
Teacher spread0.393 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
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
Published2022
Admission routes1
Has abstractyes

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