Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Death Investigation from an Historical Perspective Death Investigation from an Internations Perspective Death Investigation: Operational Rules Deaths and Other Reported Incidents Death Investigation Powers of the Coroner Death Scene Investigation Specialist Death Scenes and Investigations International Disaster Management: Mass Fatalities The Role of the Forensic Pathologist The Autopsy: Medical Issues Autopsies: Legal and Cultural Issues Identification of Human Remains Specialist Medical and Scientific Investigations The Interpretation of Injuries and Medical Findings The Medical Report and the Giving of Evidence Advocacy Inquest Hearings Inquest Findings, Recommendations and Reports Appeals, Reviews and Reopening of Inquests Death Investigation and Coroners: The Future Appendix 1 Coronial Death Investigation: Operational Activities Appendix 2 Examples of coroners' findings and recommendations Appendix 3 A coroner's information booklet Appendix 4 The Australian National Coroners Information System Appendix 5 Medical report and pro forma checklists Appendix 6 Body Charts Appendix 7 Police death notification form for the coroner Appendix 8 Quebec Code of Ethics for Coroners Appendix 9 Practice direction: Guidelines for expert witnesses in proceedings in the Federal Court of Australia
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it