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Record W2287399643

Measurement and Modeling of Polybrominated Diphenyl Ethers (PBDEs) and Polychlorinated Biphenyls (PCBs) in the Indoor Environment

2009· dissertation· en· W2287399643 on OpenAlexaboutno aff
Xianming Zhang

Bibliographic record

VenueTSpace · 2009
Typedissertation
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsnot available
Fundersnot available
KeywordsPolybrominated diphenyl ethersPolybrominated BiphenylsDiphenyl etherEnvironmental chemistryEnvironmental scienceChemistryPollutantOrganic chemistry
DOInot available

Abstract

fetched live from OpenAlex

The indoor environment is a potentially dominant source of exposure for polybrominated\ndiphenyl ethers (PBDEs) and polychlorinated biphenyls (PCBs). This thesis describes a study on\nlevels, sources, emissions, and fate of PBDEs and PCBs indoors. PBDEs and PCBs air levels in\n20 indoor environments in Toronto were sampled and measured. The geometric means of PBDE\n(Σ10BDE) and PCB (Σ35PCB) concentrations were 0.072 and 7.2 ng m-3 respectively. Statistical\nanalysis on chemical profiles distinguished the chemical sources in the 20 environments. A\nmultimedia indoor environmental model was applied on two test rooms. Estimated PBDE and\nPCB emission rates were 5.4-550 ng h-1 and 280-5870 ng h-1 respectively. Particle movement dominates within-room transport processes, and dust removal and air advection are the main chemical loss processes. Temperature, particle concentration and deposition velocity, and air\nexchange rate are the most influential parameters, which can alter source or sink behaviors of household products for the chemicals.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.094
Threshold uncertainty score0.187

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.276
Teacher spread0.252 · 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 designSimulation or modeling
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
Published2009
Admission routes1
Has abstractyes

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Same venueTSpaceSame topicToxic Organic Pollutants ImpactFrench-language works237,207