{"id":"W4389304553","doi":"10.1021/cen-10140-buscon8","title":"Dow green-lights low-carbon cracker","year":2023,"lang":"en","type":"article","venue":"C&EN Global Enterprise","topic":"Arctic and Russian Policy Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Environmental science; Carbon fibers; Waste management; Ethylene; Business; Engineering; Chemistry; Materials science; Organic chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004795591,0.0002335381,0.0001216716,0.0006082202,0.002813284,0.002230816,0.0004839927,0.001277604,0.105415],"category_scores_gemma":[0.0008685813,0.0002021609,0.00019608,0.0003841974,0.0004333065,0.0009258311,0.000728075,0.001234589,0.0174073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003222425,"about_ca_system_score_gemma":0.007104002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08153452,"about_ca_topic_score_gemma":0.2537141,"domain_scores_codex":[0.9993473,0.00002571607,0.00000985754,0.00008341548,0.0004117058,0.0001220391],"domain_scores_gemma":[0.9993968,0.00004213502,0.00001836415,0.00004292764,0.0003091895,0.0001906501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000107913,0.0001258339,0.002637504,0.00007549261,0.000006076601,0.0001794966,0.0001991528,0.0001596832,0.002826893,0.08309151,0.8179376,0.09265295],"study_design_scores_gemma":[0.000008351927,0.00002365476,0.002203393,0.00001970683,0.00000213332,0.00005673707,0.0001619863,0.0001650347,0.001349285,0.001219508,0.9947836,0.000006667557],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01707275,0.001107601,0.001282773,0.01011298,0.0006111811,0.00006298151,0.0006484707,0.0002763211,0.9688249],"genre_scores_gemma":[0.03572021,0.0007912399,0.002045455,0.002281238,0.00005495143,0.00001701978,0.0005428765,0.00008261736,0.9584644],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.105415,"threshold_uncertainty_score":0.3526483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01426583592265278,"score_gpt":0.3197433946544528,"score_spread":0.3054775587318,"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."}}