Bibliographic record
Abstract
Antimicrobial resistance is an increasing problem in healthcare institutions and in the community. Public concern about resistance is also increasing. The issue is broad and complex and not readily addressed by government, industry, or professional societies alone. On October 29-30, 1998, 19 representatives of various professional societies and governmental agencies met under the auspices of the Society for Healthcare Epidemiology of America (SHEA) at Brook Lodge Conference Center in Augusta, Michigan. The purpose of the meeting was to discuss the current status of antimicrobial resistance in the United States and Canada, including present society and governmental efforts to address the problem. Representatives exchanged experiences through presentations and discussions on the first day, then on the second day held a brainstorming session to address future needs and priorities in addressing the resistance problem. It was agreed that a national coordinated effort was needed. As part of this national effort, representatives called for the creation of a National Coalition on Antibiotic Resistance (NCAR) to combat antibiotic resistance through education, research, prevention, and advocacy. Priorities for NCAR were focused in four areas: (1) education of the public and professionals; (2) support of basic and applied research; (3) provision of an information resource and clearinghouse; and (4) advocacy initiatives. At the recommendation of the SHEA Board, discussions with the National Foundation for Infectious Diseases for the joint development of NCAR have begun.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.110 | 0.046 |
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".