Biological Detection, Identification and Monitoring (Bio DIM) in contested urban environment: leveraging standoff, point and UAS mounted particle counter/collector payload
Bibliographic record
Abstract
Detection, Identification and Monitoring (DIM) of hazardous chemical, biological, and radiological material is a critical component to Situational Awareness. Timely generated information just before and following a positive detection will lead to the most appropriate Course of Action (COA). The Technical Cooperation Program (TTCP) orchestrated a series of experiments to understand the operational limitations of new technologies in a Contested Urban Environment (CUE). One of the urban challenges occurred in Montreal, Canada in September 2018 where several technologies including a suite of biological DIM sensors were deployed. The urban environment adds complexity to the already challenging DIM task with potential line-of-sight limitations, changing wind conditions, complex communication spectrum, limited maneuverability, etc. The biological DIM suite deployed at this event included standoff, fixed point, mobile point and sampling, and identification sensing assets. The event revealed that the combination of various types of technologies might increase the overall system effectiveness. BioSense, a standoff technology, demonstrated its capacity to perform bio threat surveillance in urban environments having different constraints: short to long ranges; day and night operation; presence of various background sources; multiple surveillance areas without a deployment site having a line-of-sight on all of them and GPS-denied environment. The dedicated Chemical/Biological (CB) Sensor Data Viewer generated an integrated view of the available information from all sensors in real-time and provided a subset of this information to a central common operating software. The Class I mini UAS was equipped with an optical particle counter and filter collector membrane that was targeted to the appropriate location based on the cloud detected by the standoff sensor; and then, material classification obtained in near-real-time from the standoff spectral Laser Induced Fluorescence (LIF) interrogation was confirmed by simple post-processing of samples collected by the UAS.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".