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Record W3006390190 · doi:10.1002/mas.21624

MASS SPECTROMETRY ANALYSIS OF DRUGS OF ABUSE: CHALLENGES AND EMERGING STRATEGIES

2020· review· en· W3006390190 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

VenueMass Spectrometry Reviews · 2020
Typereview
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsBurnaby HospitalVancouver Island UniversitySimon Fraser UniversityUniversity of Victoria
Fundersnot available
KeywordsMass spectrometryChemistryDrugs of abuseGas chromatography–mass spectrometryChromatographyDrugPsychologyPsychiatry

Abstract

fetched live from OpenAlex

Mass spectrometry has been the "gold standard" for drugs of abuse (DoA) analysis for many decades because of the selectivity and sensitivity it affords. Recent progress in all aspects of mass spectrometry has seen significant developments in the field of DoA analysis. Mass spectrometry is particularly well suited to address the rapidly proliferating number of very high potency, novel psychoactive substances that are causing an alarming number of fatalities worldwide. This review surveys advancements in the areas of sample preparation, gas and liquid chromatography-mass spectrometry, as well as the rapidly emerging field of ambient ionization mass spectrometry. We have predominantly targeted literature progress over the past ten years and present our outlook for the future. © 2020 Periodicals, Inc. Mass Spec Rev.

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), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.974
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0100.003
Bibliometrics0.0030.008
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.047
GPT teacher head0.335
Teacher spread0.288 · 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