3 Royal Canadian Mounted Police, Forensic Identification Operations Support Services
Bibliographic record
Abstract
Investigating crime scenes in which chemical, biological, radiological, nuclear (CBRN) or explosive agents have been deployed poses great dangers to first responders and forensic investigators. As a result of environmental contam-ination the normal process of crime scene investigation may be harmful to the personnel involved. Nor is it always possible to remediate the scene prior to investigation as any prior decontamination of the scene to make it ‘safe’ for the investigators may destroy evidence essential for later investigation and criminal proceedings. Nor is it always practical for the crime scene to be fully processed while investigators wear appropriate protective gear. The difficulty associated with investigating contaminated crime scenes is difficult to over-estimate. Crime scenes may be sufficiently contaminated that investigators must either don highly restrictive protective suits or investigate the site via teleoperated vehicles in order to minimize the time that personnel spend in the contaminated zone. It may also be necessary to return the scene to normal use in a rather short period of time which poses additional constraints on the
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".