Spectroelectrochemical and computational studies of tetrahydrocannabinol (THC) and carboxy-tetrahydrocannabinol (THC-COOH)
Bibliographic record
Abstract
Rapid and accurate detection of tetrahydrocannabinol (THC) and its main secondary metabolite carboxy-tetrahydrocannabinol (THC-COOH) is important to ensure safe roadways and workplaces, particularly in regions of the world where cannabis use is legal. In this work, we seek to demonstrate the usefulness of electrochemical SERS (EC-SERS) for the rapid detection of both THC and THC-COOH, complemented by thorough ab initio calculations for both molecules. These results indicate that application of a voltage is essential for efficient SERS detection of cannabinoids at low concentrations in bodily fluids, allowing for the eventual development of sensitive and quantitative screening tools. To the best of our knowledge, this work represents the first EC-SERS study of both THC and THC-COOH.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".