{"id":"W2324801305","doi":"10.1177/097324700900500203","title":"Research on Identifying Important Coefficients in Chinese Sectors with High Industrial Wastewater Discharge","year":2009,"lang":"en","type":"article","venue":"Asia Pacific Business Review","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"MacEwan University","funders":"","keywords":"Wastewater; Industrial wastewater treatment; China; Secondary sector of the economy; Environmental science; Pollution; Industrial water; Government (linguistics); Business; Waste management; Environmental engineering; Engineering; Geography; Economics; Economy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.00196374,0.0002519282,0.0004169059,0.0001351286,0.0001728077,0.00008512962,0.0003183996,0.00009304986,0.001573633],"category_scores_gemma":[0.00005780638,0.0001573117,0.00005046229,0.002326544,0.0001419286,0.0002870128,0.00009094019,0.0004386904,0.0006065493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002496044,"about_ca_system_score_gemma":0.00003671493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003624005,"about_ca_topic_score_gemma":0.00007534616,"domain_scores_codex":[0.9969186,0.0004562047,0.0005796176,0.0005273714,0.0009731466,0.0005450195],"domain_scores_gemma":[0.9991521,0.00004393034,0.0001483187,0.0004965366,0.00002752888,0.0001315405],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001338474,0.008551168,0.7721373,0.004185024,0.0001568033,0.001123553,0.004432341,0.003588494,0.009242825,0.005423844,0.06410939,0.1257108],"study_design_scores_gemma":[0.001892314,0.0003104293,0.9318241,0.006533092,0.00003298018,0.00004052892,0.0002489485,0.00004697846,0.0006194248,0.0003712753,0.05733737,0.0007425844],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9844222,0.001131452,0.00004124811,0.007514777,0.0003277066,0.001296975,0.00001967511,0.00004956122,0.005196386],"genre_scores_gemma":[0.9968733,0.002041132,0.00005680251,0.0002654758,0.0000697517,0.00004495282,0.00005172673,0.00001627389,0.0005805963],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1596868,"threshold_uncertainty_score":0.999339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07833944930331728,"score_gpt":0.3530880112069129,"score_spread":0.2747485619035956,"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."}}