Reliability in Grading the Severity of Lumbar Spinal Stenosis
Bibliographic record
Abstract
Stenosis of the lumbar spinal canal is a major cause of disability and lost productivity. Computed tomography (CT) is used commonly to assess the presence and severity of spinal stensosis, because it is relatively inexpensive, readily available, and has few adverse effects. The ability of four surgeons to agree about the presence and severity of lumbar spinal stenosis based on plain CT scans was evaluated from 30 scans of varying stenosis severity (normal to severe). Kappa, a measure of chance-corrected agreement, was calculated. Surgeons exhibited moderate agreement for the presence or absence of spinal stenosis (kappa = 0.58+/-0.06). Agreement regarding the severity of stenosis, when present, was poor (kappa = 0.26+/-0.04). The ability of surgeons to agree was not improved when individual features of the CT scans were assessed (facet joint arthrosis, ligamentum flavum hypertrophy, disk protrusion, and nerve root impingement). This study suggests that CT scans are not a reliable method by which to examine the severity of lumbar spinal stenosis.
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 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 | 0.001 | 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".