{"id":"W2335834927","doi":"","title":"Opportunities for reducing volatile organic compound emissions in manufacturing office furniture partitions: a feasibility analysis","year":2009,"lang":"en","type":"article","venue":"International Conference on Energy & Environment","topic":"Indoor Air Quality and Microbial Exposure","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Christian ministry; Pollution prevention; Volatile organic compound; Plan (archaeology); Control (management); Waste management; Furniture industry; Baseline (sea); Environmental science; Environmental economics; Computer science; Operations management; Manufacturing engineering; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002461256,0.0001889748,0.0002085822,0.0001157708,0.0001490585,0.00005535552,0.0002962691,0.00009623353,0.009099203],"category_scores_gemma":[0.00002116177,0.0001871489,0.0001352402,0.00008398304,0.00009639278,0.0001840299,0.00005878013,0.0001512876,0.00003765201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004434706,"about_ca_system_score_gemma":0.00002424581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000327746,"about_ca_topic_score_gemma":0.0006339212,"domain_scores_codex":[0.9985258,0.00008472364,0.0003732413,0.0004505002,0.0003182606,0.0002474833],"domain_scores_gemma":[0.9994115,0.00006137192,0.0001348235,0.0002813034,0.000009232763,0.0001018214],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.001460311,0.005002103,0.01129052,0.0000296331,0.0009287508,0.0001577994,0.003291897,0.574366,0.2524368,0.05259913,0.00498672,0.09345031],"study_design_scores_gemma":[0.004963792,0.001510836,0.5867106,0.0003642397,0.0006425791,0.00004201361,0.004042944,0.08245394,0.1273353,0.04649923,0.1425644,0.002870113],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.963525,0.00001522511,0.01116106,0.005613783,0.0001465725,0.0002535057,0.0001399294,0.00004103871,0.01910389],"genre_scores_gemma":[0.9959052,0.00008142339,0.0007311336,0.0008257562,0.00004451859,0.00002344254,0.0002875447,0.000007363849,0.002093577],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5754201,"threshold_uncertainty_score":0.9918066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0660272524490995,"score_gpt":0.2790506540504104,"score_spread":0.2130234016013108,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}