Response to comment on “International consensus recommendations for the use of prolonged‐infusion β‐lactams endorsed by the American College of Clinical Pharmacy (<scp>ACCP</scp>), the British Society for Antimicrobial Chemotherapy (<scp>BSAC</scp>), the Cystic Fibrosis Foundation (<scp>CFF</scp>), the European Society of Clinical Microbiology and Infectious Diseases (<scp>ESCMID</scp>), the Infectious Diseases Society of American (<scp>IDSA</scp>), the Society of Critical Care Medicine (<scp>SCCM</scp>), and the Society of Infectious Diseases Pharmacists”
Bibliographic record
Abstract
We thank Mr. Cobeñas for pointing out the errors in the meta-analysis. We have repeated the meta-analysis with the corrected numbers, and the results are updated. Notably, the overall point estimates are similar to the original report. Accordingly, we have also revised the text within the evidence summary of Recommendation 7. We want to emphasize that Recommendation 7 remains unchanged as the underlying numbers still originate from the same studies, and thus, the overall quality of evidence and strength of our recommendation remain unaffected. The affected studies also were used to inform other PICOs. As such, we have also updated our loading dose subgroup analyses and corresponding text. Similar to Recommendation 7, the updated numbers and corrected meta-analysis do not alter our overall Recommendation 10 regarding use of a loading dose. An erratum will be issued. The authors declare no conflicts of interest.
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 | 0.010 | 0.103 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.031 | 0.037 |
| Insufficient payload (model declined to judge) | 0.044 | 0.038 |
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".