A Population-based Comparative Effectiveness Study of Peripheral Nerve Blocks for Hip Fracture Surgery: Erratum
Bibliographic record
Abstract
In the November 2019 issue, the article “A Population-based Comparative Effectiveness Study of Peripheral Nerve Blocks for Hip Fracture Surgery” (Hamilton GM, Lalu MM, Ramlogan R, Bryson GL, Abdallah FW, McCartney CJL, McIsaac DI: Anesthesiology 2019; 131:1025–35. doi: 10.1097/ALN.0000000000002947), costs reported in the results section of the abstract were incorrect. In the sentence “Costs were lower with a nerve block (adjusted difference, −$1,421; 95% CI, −$11,579 to −$11,289 [Canadian dollars]), but no difference in mortality (adjusted odds ratio, 0.99; 95% CI, 0.89 to 1.11) or pneumonia (adjusted odds ratio, 1.01; 95% CI, 0.88 to 1.16) was observed” the costs “−$11,579 to −$11,289” should read “−$1,579 to −$1,289.” The correct sentence reads: “Costs were lower with a nerve block (adjusted difference, −$1,421; 95% CI, −$1,579 to −$1,289 [Canadian dollars]), but no difference in mortality (adjusted odds ratio, 0.99; 95% CI, 0.89 to 1.11) or pneumonia (adjusted odds ratio, 1.01; 95% CI, 0.88 to 1.16) was observed.”The publisher regrets this error. The article has been corrected online and in the PDF.
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 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 | 0.051 | 0.217 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.008 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 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".