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Record W7100731217

from "Determination of Organic Contaminants in Residential Indoor Air Using an Adsorption-Thermal

2015· article· en· W7100731217 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsnot available
Fundersnot available
KeywordsSorbentContaminationIndoor airDesorptionVolatile organic compoundCartridge
DOInot available

Abstract

fetched live from OpenAlex

This field study evaluated the ablllty of a multl-sorbent sampllng tubelthermal desorption technique to identlfy and to provide quantltatlve data on volatile organic contaminants in indoor air. Air samples, from 12 Canadian homes, were collected on multllayer sorbent cartridges and analyzed using Adsorptlon/Thermal Desorptlon coupled wlth Gas Chromatog-raphy/Mass Spectrometry. The study Included the ldentlficatlon and quantltatlon of 23 target compounds. Analysis of sorbent tubes fortified wlth these target compounds lndlcated that recoveries were>70 percent and the precision was usually better than 15 percent. These organic compounds were found to be stable on the sorbent tubes for at least seven days. With some exceptions, the target compounds were usually detected at 1 to 10 pg/m3 in indoor alr samples; other organics ldentlfied qualltatlvely were saturated hydrocarbons, unsaturated hydrocarbons, cycllc hydrocarbons, substituted aromatics, oxygenates, some halogenates and cycllc species such as camphenes/plnenes and carenes.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.109
Threshold uncertainty score0.216

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.037
GPT teacher head0.279
Teacher spread0.242 · 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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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