Bibliographic record
Abstract
The discovery three months ago of the first person in the U.S. infected with Escherichia coli that carries the mcr-1 gene set off alarms among researchers fighting antibiotic resistance. Six months prior, Chinese scientists had found that the gene imparts bacterial resistance to colistin, a 50-year-old polymyxin antibiotic. Colistin-resistant bacteria have also been identified in Europe and Canada. Although colistin fell out of favor in the 1970s because of its toxicity, it has become a drug of last resort against multi-drug-resistant infections. This last line of defense is now under attack. Antibiotic-resistant pathogens already cause at least 2 million illnesses and 23,000 deaths each year in the U.S., according to the U.S. Centers for Disease Control & Prevention, with a similar number of deaths occurring in Europe as well. CDC considers three—Clostridium difficile, carbapenem-resistant Enterobacteriaceae, and drug-resistant Neisseria gonorrhoeae—as urgent threats. Among the next level of serious threats are drug-resistant
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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.011 | 0.015 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.062 | 0.026 |
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".