Threshold(trade mark) Immunoassays for Identification of Biological Agents: NATO SIBCA Exercise III
Bibliographic record
Abstract
In February 2001, the NATO Panel VII Subgroup on Sampling and Identification of Biological and Chemical Agents (SIBCA) conducted the third international training exercise on the identification of biological agents. Fourteen NATO national laboratories participated: Austria, Bulgaria, Canada, France, Germany (two laboratories), Italy, the Netherlands, Norway, Poland, Sweden, the United Kingdom and the United States (two laboratories). The designated laboratory for Canada was Defence R&D Canada - Suffield (DRDC Suffield). Participant laboratories were sent seven samples, four liquid (including one buffer blank) and three solid, consisting of soil. Participants were advised that samples could contain any one of the following gamma-irradiated organisms: Bacillus anthracis, Yersinia pestis, Brucella melitensis, Francisella tularensis, Vibrio cholera, Burkholderia mallei; Venezuelan equine encephalitis (VEE) virus, Vaccinia virus, Coxiella burnetti, or Yellow fever virus. A number of immunologically-based technologies were used at DRDC Suffield for screening of sample unknowns, one of which was the Threshold(TM) assay, a Light Addressable Potentiometric Sensor (LAPS) assay. Antigen capture Threshold(TM) assays were available for five biological agents: Bacillus anthracis, Yersinia pestis, Brucella melitensis, Francisella tularensis, and Burkholderia mallet. Two biological agents were identified by Threshold(TM), both from the liquid samples (B. melitensis and F. tularensis). No "false positive" or "false negative" reactions were observed with SIBCA liquid samples. However, soil-extracted samples produced multiple "false positive" reactions and one "false negative" reaction, making identification of agents from this medium impossible to achieve.
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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 | 0.044 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.012 |
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".