Bibliographic record
Abstract
PulseNet is the national molecular subtyping network for foodborne disease surveillance established by the Centers for Disease Control and Prevention with assistance from the Association of Public Health Laboratories. Dr. Bala Swaminathan, chief of the Foodborne and Diarrheal Diseases Laboratory Section, is the principal architect of PulseNet. The program, which began in 1996 with 10 laboratories typing a single pathogen (Escherichia coli 0157:H7) now includes 46 state and 2 local public health laboratories and the food safety laboratories of the U.S. Food and Drug Administration and the U.S. Department of Agriculture. By the end of 2001 all 50 state laboratories will participate in PulseNet. In 2000, Canada became the first international PulseNet participant with the formation of PulseNet North. The National Laboratory for Enteric Pathogens, Winnipeg, Manitoba coordinates the standardized subtyping of foodborne pathogenic bacteria by PulseNet protocols in 6 provincial laboratories. Four foodborne pathogens (E.coli 0157:H7, non-typhoid Salmonella serotypes, Listeria monocytogenes and Shigella) are being subtyped using standardized Pulsed Field Gel Electrophoresis (PFGE) protocols. Other bacterial, viral and parasitic organisms will be added soon. PulseNet plays a significant role in the detection, investigation and control of outbreaks. Continued on page 3...Page 2
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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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.239 | 0.157 |
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".