MétaCan
Menu
Back to cohort
Record W4409690771 · doi:10.1002/jssc.70138

Are We Ready for It? A Review of Forensic Applications and Readiness for Comprehensive Two‐Dimensional Gas Chromatography in Routine Forensic Analysis

2025· review· en· W4409690771 on OpenAlex
Emma L. Macturk, Kevin Hayes, Gwen O'Sullivan, Katelynn A. Perrault

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Separation Science · 2025
Typereview
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsMount Royal University
Fundersnot available
KeywordsForensic scienceGas chromatographyArsonChromatographyComputer scienceChemistryBiochemical engineeringEngineeringLaw

Abstract

fetched live from OpenAlex

Comprehensive two-dimensional gas chromatography (GC×GC) has been explored in forensic research to provide advanced chromatographic separation for forensic evidence, including illicit drugs, fingerprint residue, chemical, biological, nuclear, and radioactive (CBNR) substances, toxicological evidence, odor decomposition, and petroleum analysis for arson investigations and oil spill tracing. In GC×GC, the separation and analysis of analytes is similar to one-dimensional GC, but the primary column is connected to a secondary column via a modulator to provide two independent separation mechanisms, thus increasing the peak capacity of the analysis. The goal of implementing GC×GC in forensic studies is often to increase the separation and detectability of analytes and has most often been applied in nontargeted forensic applications where a wide range of analytes must be analyzed simultaneously. To date, there has been no summary of the current state of forensic research that evaluates both analytical and legal readiness for routine use. For these analytical methods to be adopted into forensic laboratories and be used in evidence analysis, they must meet rigorous analytical standards. In addition, new analytical methods for evidence analysis must adhere to standards laid out by the legal system, including the Frye Standard, Daubert Standard, and Federal Rule of Evidence 702 in the United States and the Mohan Criteria in Canada. Current research on GC×GC use for forensic applications was summarized and reviewed for analytical advances and technology readiness to provide a comprehensive view of GC×GC use for future routine implementation. A technology readiness scale, with levels from 1 to 4, was used to characterize the advancement of research in each individual application area. Seven forensic chemistry applications are discussed related to courtroom criteria and categorized into technology readiness levels based on current literature as of 2024. Future directions for all applications should place a focus on increased intra- and inter-laboratory validation, error rate analysis, and standardization.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.617
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.004
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.075
GPT teacher head0.418
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it