MétaCan
Menu
Back to cohort
Record W2470902106

Screening of options for VOC emissions reductions in manufacturing office furniture partitions

2008· article· en· W2470902106 on OpenAlexaffabout
Frank S. Luisser, Marc A. Rosen

Bibliographic record

VenueInternational Conference on Energy & Environment · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Impact and Sustainability
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsChristian ministryPollution preventionFurniture industryPlan (archaeology)Air pollutionWaste managementPollutionBaseline (sea)Volatile organic compoundEnvironmental scienceManufacturingEnvironmental economicsOperations managementBusinessEngineeringManufacturing engineering
DOInot available

Abstract

fetched live from OpenAlex

Volatile organic compound (VOC) emission reduction options in manufacturing office furniture partitions are screened using the pollution prevention (P2) methodology as defined by the Ontario Ministry of the Environment. The purpose is to identify viable options that can allow a VOC P2 plan for manufacturing office furniture partitions to be developed. The concepts also apply generally to the wood furniture industry. Baseline VOC emissions for a typical plant are estimated using a mass balance approach. Pollution prevention measures are identified and screened using realistic criteria and weightings. Several measures are deemed viable, including implementing several best management practices, not painting of non-visible parts, switching gluing processes, recycling solvent and modifying attachments. A feasibility analysis is performed in a follow-up article for the screened measures based on technical, environmental and economic considerations.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.041
GPT teacher head0.272
Teacher spread0.231 · 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 designNot applicable
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
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueInternational Conference on Energy & EnvironmentSame topicEnvironmental Impact and SustainabilityFrench-language works237,207