MétaCan
Menu
Back to cohort
Record W2919280075 · doi:10.1167/iovs.18-25955

IMI – Clinical Myopia Control Trials and Instrumentation Report

2019· review· en· W2919280075 on OpenAlexaff
James S. Wolffsohn, Pete Kollbaum, David A. Berntsen, David A. Atchison, Alexandra Benavente-Pérez, Arthur Bradley, Hetal Buckhurst, Michael J. Collins, Takashi Fujikado, Takahiro Hiraoka, Masakazu Hirota, Debbie Jones, Nicola S. Logan, Linda Lundström, Hidemasa Torii, Scott A. Read, Kovin Naidoo

Bibliographic record

VenueInvestigative Ophthalmology & Visual Science · 2019
Typereview
Languageen
FieldMedicine
TopicOphthalmology and Visual Impairment Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMedicineInstrumentation (computer programming)Clinical trialRefractive errorOptometryOphthalmologyMedical physicsPhysical therapyEye diseaseComputer scienceInternal medicine

Abstract

fetched live from OpenAlex

The evidence-basis based on existing myopia control trials along with the supporting academic literature were reviewed; this informed recommendations on the outcomes suggested from clinical trials aimed at slowing myopia progression to show the effectiveness of treatments and the impact on patients. These outcomes were classified as primary (refractive error and/or axial length), secondary (patient reported outcomes and treatment compliance), and exploratory (peripheral refraction, accommodative changes, ocular alignment, pupil size, outdoor activity/lighting levels, anterior and posterior segment imaging, and tissue biomechanics). The currently available instrumentation, which the literature has shown to best achieve the primary and secondary outcomes, was reviewed and critiqued. Issues relating to study design and patient selection were also identified. These findings and consensus from the International Myopia Institute members led to final recommendations to inform future instrumentation development and to guide clinical trial protocols.

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)0.024
metaresearch head score (Gemma)0.066
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.024
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.066
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0080.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.002

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 head0.297
GPT teacher head0.545
Teacher spread0.248 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations188
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueInvestigative Ophthalmology & Visual ScienceSame topicOphthalmology and Visual Impairment StudiesFrench-language works237,207