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A Comparison of Paired Calibration Check Results of<i>Alco-Sensor IV- RBT IV</i>and<i>Intoxilyzer® 5000 C</i>in Real Cases

2013· article· en· W2164722157 on OpenAlexaffvenueabout
Jacques Tremblay

Bibliographic record

VenueCanadian Society of Forensic Science Journal · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced Chemical Sensor Technologies
Canadian institutionsConcordia University
Fundersnot available
KeywordsSignificant differenceMathematicsCalibrationStatisticsMean differenceZero (linguistics)Analytical Chemistry (journal)ChemistryChromatographyConfidence interval

Abstract

fetched live from OpenAlex

More than 1600 paired-control tests data obtained on Alco-Sensor IV—RBTIV and Intoxilyzer® 5000 C have been reviewed. A quasi-normal distribution around the target value of 100 mg/100 mL was observed. Moreover, not only are instruments accurate, but they are also stable. In sequences of tests in real cases, paired data comparison of first (CTRL1) and second (CTRL2) control results showed a difference (CTRL1—CTRL2) of zero in about one-third (⅓) of assays. The majority of cases (98.5%) were found to have a cumulative absolute difference of 3 mg/100 mL. In just one case, the difference between CTRL1 and CTRL2 was 10 mg/100 mL, the maximum acceptable in Quebec. Thus, although calibration checks of 95 to 105 mg/100 mL are acceptable, measurement uncertainty of these instruments should be considered well below 10 mg/100 mL in the great majority of 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.026
GPT teacher head0.264
Teacher spread0.238 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

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Citations0
Published2013
Admission routes3
Has abstractyes

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Same venueCanadian Society of Forensic Science JournalSame topicAdvanced Chemical Sensor TechnologiesFrench-language works237,207