Ottawa classification for symptomatic acetabular dysplasia assessment of interobserver and intraobserver reliability
Bibliographic record
Abstract
AIMS: The aim of the current study was to assess the reliability of the Ottawa classification for symptomatic acetabular dysplasia. METHODS: In all, 134 consecutive hips that underwent periacetabular osteotomy were categorized using a validated software (Hip2Norm) into four categories of normal, lateral/global, anterior, or posterior. A total of 74 cases were selected for reliability analysis, and these included 44 dysplastic and 30 normal hips. A group of six blinded fellowship-trained raters, provided with the classification system, looked at these radiographs at two separate timepoints to classify the hips using standard radiological measurements. Thereafter, a consensus meeting was held where a modified flow diagram was devised, before a third reading by four raters using a separate set of 74 radiographs took place. RESULTS: Intrarater results per surgeon between Time 1 and Time 2 showed substantial to almost perfect agreement among the raters (κappa = 0.416 to 0.873). With respect to inter-rater reliability, at Time 1 and Time 2 there was substantial agreement overall between all surgeons (Time 1 κappa = 0.619; Time 2 κappa = 0.623). Posterior and anterior rating categories had moderate and fair agreement at Time 1 (posterior κappa = 0.557; anterior κappa = 0.438) and Time 2 (posterior κappa = 0.506; anterior κappa = 0.250), respectively. At Time 3, overall reliability (κappa = 0.687) and posterior and anterior reliability (posterior κappa = 0.579; anterior κappa = 0.521) improved from Time 1 and Time 2. CONCLUSION: 2020;9(5):242-249.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.037 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".