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Record W7099170027

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2015· article· en· W7099170027 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMathematics
TopicMathematics Education and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsSkewnessDistribution (mathematics)Test (biology)Breath testSignificant difference
DOInot available

Abstract

fetched live from OpenAlex

A one-year retrospective study was conducted of 2,759 duplicate lntoxilyzer @ 5000C test results in the City of Toronto during 1995 with a statutory wait of "at least fif-teen minutes " between tests. The time between tests ranged from 19 to 73 minutes (median = 22 minutes). The absolute difference between the first and second breath tests ranged from 0 to 0.042 91210 L (median 0.007 9/21 0 L). The distribution of these differences was not normal (KS = 0.1566, skewness =-0.1 143). The differences between the truncated first and second tests were not within the recommended 0.02 91210 L in 7.5 % of the paired data. The second test was 2 0.01 91210 L less than the first breath test in 35 % of the cases (n=981) but was 2 0.01 91210 L greater than the first breath test in only 7 % (n=203) using truncated results. The observed skewness in this distribution is likely due to the elimination of alcohol that occurred during the time between tests. Following the adjustment of the second test to account for the mean pharmacokinetic alcohol elimination rate in drinking drivers, the distribution represented by the difference between the two tests still represented a non-normal

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.389
Threshold uncertainty score0.999

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)0.0020.000

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 head0.359
GPT teacher head0.462
Teacher spread0.102 · 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.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations0
Published2015
Admission routes1
Has abstractyes

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