Application of professional best practices in postmortem forensic toxicology
Bibliographic record
Abstract
Postmortem forensic toxicology plays a critical role in medicolegal death investigations through the identification and quantitation of drugs and other substances in postmortem fluids and tissues. Due to the complexity of this sub-discipline, consistent application of best practices is critical for ensuring accurate and reliable results, particularly in the context of challenges such as emerging novel psychoactive substances, complex poly-drug interactions, postmortem drug redistribution, and analytical limitations inherent with postmortem specimens. Although there has been significant progress in the development of consensus-based forensic toxicology standards, their scope is intentionally broad to accommodate human performance, postmortem, regulated and non-regulated employment drug testing, court-ordered toxicology, and other applications. Consequently, some aspects specific to postmortem toxicology and medicolegal death investigation are not addressed within the standards. This manuscript seeks to fill these gaps by demonstrating how current standards can be applied in a postmortem toxicology setting and presenting best practices in situations where no established standards exist. These best practices will aid laboratories in prioritizing changes to workflows, allocating resources more efficiently, improving analytical accuracy and reproducibility, ensuring interpretative consistency, and strengthening forensic defensibility in administrative and legal proceedings. Key topics addressed include specimen collection and case submission protocols, method validation approaches tailored for postmortem analysis, optimized analytical workflows based on testing scope and case classification, and quality assurance requirements. Considerations for data review, reporting, and result interpretation are discussed in the context of accurate determination of cause and manner of death. Emphasis is placed on integrating toxicological findings with investigative and autopsy information obtained through ongoing communication with stakeholders. By integrating the application of existing consensus standards with the best community practices for postmortem toxicology, this manuscript aims to support the generation of robust and reliable toxicological data, with the goal of improving forensic investigations, public health surveillance, and drug policy development.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 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".