MétaCan
Menu
Back to cohort
Record W2167333732 · doi:10.1139/s06-022

Indoor and outdoor SO<sub>2</sub> in a community near oil sand extraction and production facilities in northern Alberta

2006· article· en· W2167333732 on OpenAlexvenueaboutno aff
Warren B. Kindzierski, Harbinder K. Sunita. Ranganathan

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceYardSampling (signal processing)Sulfur dioxideIndoor air qualityHydrology (agriculture)Environmental engineeringEcologyEngineeringTelecommunications

Abstract

fetched live from OpenAlex

A baseline study measuring indoor and outdoor sulfur dioxide (SO2) levels was undertaken in a small native community (Fort McKay) in northern Alberta. The objective was to assess whether proximity of numerous oil sand operations affected air quality in the community. A passive sampling device was deployed for 96 h durations at 30 randomly selected homes over a 6 week period such that 75% of homes were sampled during weekdays and 25% during weekends. The common living area of each home (kitchen or family room) was sampled indoors. Outdoor passive samplers were attached to a sampling stand under a shelter in the yard. Indoor SO2 levels were all less than a method detection limit of 1.3 µg/m3 (n = 30). The median outdoor level was 1.7 µg/m3 (n = 28, range 1.3 to 3.7 µg/m3, 70% > method detection level). Results of testing to determine accuracy and precision of the monitors showed both measures to be within 35% based on a 96 h average measurement. Overall, these levels are considered very low and consistent with levels observed elsewhere in Alberta. Key words: sulfur dioxide, passive sampling, indoor and outdoor air.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.179

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.010
GPT teacher head0.219
Teacher spread0.209 · 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

Citations14
Published2006
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Environmental Engineering and ScienceSame topicAir Quality and Health ImpactsFrench-language works237,207