MétaCan
Menu
Back to cohort
Record W1966995070 · doi:10.1002/elps.200500886

Analysis of amphetamine, methamphetamine and methylenedioxy‐methamphetamine by micellar capillary electrophoresis using cation‐selective exhaustive injection

2006· article· en· W1966995070 on OpenAlex

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.

Bibliographic record

VenueElectrophoresis · 2006
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMicellar electrokinetic chromatographyChemistryChromatographyCapillary electrophoresisMethylenedioxySodium dodecyl sulfateMethamphetamineAmphetamineDetection limitElectrolytePharmacologyOrganic chemistry

Abstract

fetched live from OpenAlex

Cation-selective exhaustive injection (CSEI) is used as an on-line concentration method for the high-sensitivity analysis of illicit amphetamines using CE. Optimum conditions for the determination of amphetamine, methamphetamine and methylenedioxy-methamphetamine were investigated. Sodium dodecyl sulfate (25 mM) in 100 mM phosphate buffer (pH 2.9) with 20% methanol as organic additive was used as the background electrolyte for CE separation. The LOD, based on an S/N of 3:1, was about 0.01 microg/mL using normal capillary micellar electrokinetic chromatography, while by using CSEI in combination with micellar sweeping the sensitivity increased up to 1000-fold with the LOD lower than 50 pg/mL. The reproducibility of CSEI combined with micellar sweeping for analyzing amphetamines was satisfactory (relative standard deviation around 10% by using area ratios against an internal standard). This method is highly sensitive and can be used to analyze trace amount amphetamines in human hair.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.006
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.004
GPT teacher head0.197
Teacher spread0.193 · 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