The OSCAR-IB Consensus Criteria for Retinal OCT Quality Assessment
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Full frame distilled prediction
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.
- Candidate categories
- none
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: ObservationalConsensus signal: Observational
- Genre
- Candidate signal: EmpiricalConsensus signal: Empirical
- Teacher disagreement score
- 0.216
- Threshold uncertainty score
- 0.285
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.250 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
Abstract
BACKGROUND: Retinal optical coherence tomography (OCT) is an imaging biomarker for neurodegeneration in multiple sclerosis (MS). In order to become validated as an outcome measure in multicenter studies, reliable quality control (QC) criteria with high inter-rater agreement are required. METHODS/PRINCIPAL FINDINGS: A prospective multicentre study on developing consensus QC criteria for retinal OCT in MS: (1) a literature review on OCT QC criteria; (2) application of these QC criteria to a training set of 101 retinal OCT scans from patients with MS; (3) kappa statistics for inter-rater agreement; (4) identification reasons for inter-rater disagreement; (5) development of new consensus QC criteria; (6) testing of the new QC criteria on the training set and (7) prospective validation on a new set of 159 OCT scans from patients with MS. The inter-rater agreement for acceptable scans among OCT readers (n = 3) was moderate (kappa 0·45) based on the non-validated QC criteria which were entirely based on the ophthalmological literature. A new set of QC criteria was developed based on recognition of: (O) obvious problems, (S) poor signal strength, (C) centration of scan, (A) algorithm failure, (R) retinal pathology other than MS related, (I) illumination and (B) beam placement. Adhering to these OSCAR-IB QC criteria increased the inter-rater agreement to kappa from moderate to substantial (0.61 training set and 0.61 prospective validation). CONCLUSIONS: This study presents the first validated consensus QC criteria for retinal OCT reading in MS. The high inter-rater agreement suggests the OSCAR-IB QC criteria to be considered in the context of multicentre studies and trials in MS.
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.
The record
- Venue
- PLoS ONE
- Topic
- Glaucoma and retinal disorders
- Field
- Medicine
- Canadian institutions
- University of Calgary
- Funders
- Gemeinnützige Hertie-StiftungVanderbilt University Medical Center
- Keywords
- KappaMedicineOptical coherence tomographyProspective cohort studyCohen's kappaRetinalMedical physicsArtificial intelligenceSet (abstract data type)Computer scienceOphthalmologyPathologyMachine learningMathematics
- Has abstract in OpenAlex
- yes