MétaCan
Menu
Back to cohort
Record W2135127426 · doi:10.1039/b510084d

Cross-sensitivities of electrochemical detectors used to monitor worker exposures to airborne contaminants: False positive responses in the absence of target analytes

2005· article· en· W2135127426 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Environmental Monitoring · 2005
Typearticle
Languageen
FieldChemical Engineering
TopicChemical Safety and Risk Management
Canadian institutionsInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du TravailUniversité du Québec à MontréalUniversité du Québec à Trois-Rivières
FundersConcordia UniversityInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail
KeywordsAnalyteDetectorEnvironmental scienceContaminationEnvironmental chemistryChemistryChromatographyComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

Ideally, the response of electrochemical detectors is proportional to the concentration of targeted airborne chemicals and is not be affected by concomitantly present substances. Manufacturers provide a limited list of cross-sensitivities but end-users have anecdotally reported unexpected interferences by other substances. Electrochemical detectors designed to measure airborne levels of CO, H(2)S, NO, NO(2), or SO(2), were challenged with potentially interfering substances in the absence of target analytes. Cross-sensitivities undocumented by the manufacturers were observed and were found to vary between different models of instruments for the same challenge chemical.

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 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 score0.250
Threshold uncertainty score0.596

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.009
GPT teacher head0.252
Teacher spread0.243 · 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