Bibliographic record
Abstract
The development of antibiotics is one of the greatest advances of modern medicine. While antibiotics have dramatically improved morbidity and mortality rates worldwide, current evidence asserts that one should err on the side of caution when prescribing antibiotics. The medical literature is accumulating studies on alarming consequences of inappropriate antibiotic use. Due to antibiotic overexposure, a North American “hypervirulant” strain of Clostridium difficile has emerged causing more severe gastrointestinal manifestations than previous strains. More recently, antibiotic overuse has been associated with obesity and diabetes mellitus. Unnecessary antibiotic use has led to increasing rates of bacterial resistance rendering more antibiotics ineffective. We are currently on the brink of an era which could reverse all the progress made with the introduction of antibiotics. The salient health consequences of inappropriate antibiotic prescriptions and the threat of a postantibiotic era command attention to practical initiatives that improve antibiotic prescribing patterns.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.046 | 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".