Bibliographic record
Abstract
Drink Safe Technology Version 1.2 is an inexpensive color-change reagent test marketed internationally for use by consumers in settings such as a night club to detect potentially incapacitating concentrations of gamma-hydroxybutyric acid (GHB) and ketamine in beverages. The objective of this study was to compare product performance in the laboratory and performance in the hands of consumers in the field. Product performance in the laboratory adhered to the protocol defined by the manufacturer. Product performance in the hands of consumers in field settings allowed browsing participants to pipette an aliquot of their own drinks into randomly coded vials containing authentic drugs, or pure water, so as to yield the same concentrations of GHB or ketamine specified in the manufacturer-defined protocol, or blanks. Consumers were to proceed according to the directions printed on the product, and to record their results on a card with a code corresponding with the vial to which they had added an aliquot of their beverage. Diagnostic performance was calculated using two-way analysis. In the laboratory, Drink Safe Technology Version 1.2 reliably detected GHB and ketamine at concentrations specified by the manufacturer's protocol. The reactive color change denoting a positive test for GHB was rapid, but a positive test for ketamine required substantially more time to resolve. Nonetheless, test accuracy following the manufacturer's protocol in the laboratory was 100%. In the field, based on 101 paired-test results recorded by consumers, the test efficiency was 65.1%, sensitivity 50%, and specificity 91.6%. The product performed much better in the laboratory than it did in the hand of consumers in the field. There seems to be considerable potential for consumers to misinterpret a test result. The potential for consumers to record a false-negative test result for a spiked drink is cause for concern.
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 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".