Bibliographic record
Abstract
Erythromycin, which was introduced over 50 years ago, was the first macrolide to be used clinically. "New" macrolides, for the treatment of patients with various infectious diseases, were not clinically introduced until 40 years later. The pharmacokinetic and adverse events profile of erythromycin initially limited its use to an alternative agent for patients with allergy to beta-lactam agents. However, the emergence of atypical and/or new pathogens and the ongoing escalation of acquired antimicrobial resistance has impacted on the empirical and organism directed therapy of infectious diseases. Azithromycin and clarithromycin were developed by enhancing the basic macrolide structure. Some of the basic features associated with these new agents include a pharmacokinetic profiles that allow once or twice daily dosing with a much lower incidence of side effects and a substantially broader spectrum of activity which includes some Gram-negative bacilli, atypical pathogens and new, unconventional or uncommon pathogens. Clinical trial data has supported the use of "new" macrolides in a wide range of clinical indications, however, some specific indications are currently restricted to treatment with either azithromycin or clarithromycin. Macrolide resistance is a class effect and depending on the mechanism will confer either low or high level resistance. While resistance is problematic, it does not always result in clinical failure. The macrolides are a valuable class of antimicrobial agent and play an important role in the management of infectious diseases.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.006 |
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".