Erratum to: How Successful Is Antibiotic Treatment for Superficial Surgical Site Infections After Open Fracture? A Fluid Lavage of Open Wounds (FLOW) Cohort Secondary Analysis
Bibliographic record
Abstract
There are two errors in the published study, “How Successful Is Antibiotic Treatment for Superficial Surgical Site Infections After Open Fracture? A Fluid Lavage of Open Wounds (FLOW) Cohort Secondary Analysis”. The CI range in the Results section of the Abstract is incorrect as published. The sentence should be: “After controlling for potential confounding variables, such as age, fracture severity, and time from injury to initial surgical irrigation and debridement, superficial SSIs diagnosed later in follow-up were associated with antibiotics not resolving the SSI (odds ratio 1.05 [95% CI 1.002 to 1.10] for every week of follow-up; p = 0.04).” Additionally, the CI range in the first sentence under the Factors Associated with Antibiotics Not Resolving Superficial SSIs subhead in the Results section is incorrect. The sentence should be: After controlling for potential confounding variables such as age, fracture severity, and time from injury to initial surgical irrigation and débridement, superficial SSIs that were diagnosed later in follow-up were associated with antibiotics not resolving the SSI (OR 1.05 [95% CI 1.002 to 1.10] for every week of follow-up; p = 0.04). Clinical Orthopaedics and Related Research® apologizes for the errors.
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 | 0.038 | 0.270 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.039 | 0.016 |
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".