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CPD: How clinical science translates into clinical practice

2023· article· en· W4404242870 on OpenAlexaff
Nicola S. Logan

Bibliographic record

VenueOptician · 2023
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Visual Impairment Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsClinical PracticeComputer scienceData sciencePsychologyMedical physicsMedical educationMedicineFamily medicine

Abstract

fetched live from OpenAlex

Professor Debbie Jones and Professor Nicola Logan take a close look at what can be learned from the results of the MiSight 1 day clinical study after seven years and how this might influence our clinical practice. (C105432, suitable for logging as one distance learning CPD point for optometrists, contact lens opticians and dispensing opticians)

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)0.271
metaresearch head score (Gemma)0.540
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.271
Threshold uncertainty score0.900

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2710.540
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0130.007
Science and technology studies0.0060.044
Scholarly communication0.0510.039
Open science0.0050.019
Research integrity0.0150.026
Insufficient payload (model declined to judge)0.0120.006

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 head0.149
GPT teacher head0.541
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
Domainnot available
GenreCommentary

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
Published2023
Admission routes1
Has abstractyes

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