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Ability of Commercially Available “Date-Rape” Drug Test Kits to Detect Gamma-Hydroxybutyrate in Popular Drinks

2007· article· en· W2138011614 on OpenAlexaffvenue
Anne Marie Child, Peter Child

Bibliographic record

VenueCanadian Society of Forensic Science Journal · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIdentification and Quantification in Food
Canadian institutionsCooke Aquaculture (Canada)
Fundersnot available
KeywordsGamma hydroxybutyrateToxicologyMedicineFood scienceChemistryPharmacologyBiology

Abstract

fetched live from OpenAlex

Gamma-hydroxybutyrate (GHB) is one of the most widely-used drugs for drink adulteration in “date-rape” cases. Several test kits have been introduced to detect GHB in drinks. These include “DrinkSafe™” cards, “DrinkSafe™” coasters, and “Drink Detective™” test kits. This work was conducted to determine how well the available kits detect GHB in a variety of beverages. Using synthetic GHB in pure water, all three test kit types gave a positive blue response. No false negatives were observed. Gamma-butyrolactone and water gave no response on any of the kits. Experiments with beverages containing GHB focussed on the “DrinkSafe™” products because they provide two test areas on each card, allowing spiked and un-spiked beverages to be compared directly. Using the original green colour of the “DrinkSafe™” products as a reference, seven of the eleven drinks gave an obvious blue reaction with the cards and nine of eleven with the coasters. In both cases, GHB-spiked Cosmopolitan and Margarita samples gave false negatives. With all beverages, however, the control drink changed the colour of the test spot. This reproducible difference in colour between the control and the spiked samples suggests that by putting an unadulterated sample of drink onto the test card, an individual could greatly increase their chances of detecting GHB in their beverage. Despite some limitations, the low cost of the kits and their apparent reliability suggest that they would be a useful screening tool for officials investigating rape cases.

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 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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.017
GPT teacher head0.268
Teacher spread0.251 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2007
Admission routes2
Has abstractyes

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