Evaluating Agreement: Conducting a Reliability Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Instruments that are useful in clinical or research practice will, when the object of measurement is stable, yield similar results when applied at different times, in different situations, or by different users. Studies that measure the relation of differences between patients or subjects and measurement error (reliability studies) are becoming increasingly common in the orthopaedic literature. In this paper, we identify common aspects of reliability studies and suggest features that improve the reader's confidence in the results. One concept serves as the foundation for all further consideration: in order for a reliability study to be relevant, the patients, raters, and test administration in the study must be similar to the clinical or research context in which the instrument will be used. We introduce the statistical measures that readers will most commonly encounter in reliability studies, and we suggest an approach to sample-size estimation. Readers interested in critically appraising reliability studies or in developing their own reliability studies may find this review helpful.
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.
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 | 0.080 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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)
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