Spectrum bias, a common unrecognised issue in orthopaedic agreement studies
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Bibliographic record
Abstract
OBJECTIVES: Current studies on the additional benefit of using computed tomography (CT) in order to evaluate the surgeons' agreement on treatment plans for fracture are inconsistent. This inconsistency can be explained by a methodological phenomenon called 'spectrum bias', defined as the bias inherent when investigators choose a population lacking therapeutic uncertainty for evaluation. The aim of the study is to determine the influence of spectrum bias on the intra-observer agreement of treatment plans for fractures of the distal radius. METHODS: Four surgeons evaluated 51 patients with displaced fractures of the distal radius at four time points: T1 and T2: conventional radiographs; T3 and T4: radiographs and additional CT scan (radiograph and CT). Choice of treatment plan (operative or non-operative) and therapeutic certainty (five-point scale: very uncertain to very certain) were rated. To determine the influence of spectrum bias, the intra-observer agreement was analysed, using Kappa statistics, for each degree of therapeutic certainty. RESULTS: In cases with high therapeutic certainty, intra-observer agreement based on radiograph was almost perfect (0.86 to 0.90), but decreased to moderate based on a radiograph and CT (0.47 to 0.60). In cases with high therapeutic uncertainty, intra-observer agreement was slight at best (-0.12 to 0.19), but increased to moderate based on the radiograph and CT (0.56 to 0.57). CONCLUSION: Spectrum bias influenced the outcome of this agreement study on treatment plans. An additional CT scan improves the intra-observer agreement on treatment plans for a fracture of the distal radius only when there is therapeutic uncertainty. Reporting and analysing intra-observer agreement based on the surgeon's level of certainty is an appropriate method to minimise spectrum bias. Cite this article: Bone Joint Res 2015;4:190-194.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.052 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it