{"id":"W2791711244","doi":"10.3390/su10040962","title":"A Sustainable Industry-Environment Model for the Identification of Urban Environmental Risk to Confront Air Pollution in Beijing, China","year":2018,"lang":"en","type":"article","venue":"Sustainability","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Beijing; China; Sustainable development; Air pollution; Environmental pollution; Environmental planning; Identification (biology); Pollution; Business; Sustainable city; Environmental protection; Environmental science; Civil engineering; Engineering; Urban planning; Geography; Political science","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003180202,0.0003573331,0.0003439916,0.0001023095,0.0005956882,0.00003413889,0.0006079985,0.0002842581,0.0004851096],"category_scores_gemma":[0.001044422,0.000300842,0.000183113,0.000336461,0.001553659,0.0004799331,0.0006843904,0.0004459306,0.00003442683],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007111222,"about_ca_system_score_gemma":0.0001107738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002494485,"about_ca_topic_score_gemma":0.0002709909,"domain_scores_codex":[0.9964015,0.0002729607,0.0009233669,0.0008543336,0.0005555141,0.0009923597],"domain_scores_gemma":[0.9980424,0.0001099739,0.0003669537,0.001205866,0.0000333514,0.0002414467],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004527164,0.0009131985,0.8009774,0.00008194602,0.00002364393,0.000002246689,0.009168777,0.1818923,0.0009132008,0.0007731208,0.001199539,0.00360187],"study_design_scores_gemma":[0.0006973573,0.0003997508,0.9024653,0.000004046021,0.00005190514,0.000001244858,0.009701635,0.07155181,0.001731567,0.009768683,0.003297264,0.000329375],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9641215,0.00004581343,0.02907447,0.002340005,0.00005571755,0.004022807,0.0001007171,0.00003003854,0.0002089341],"genre_scores_gemma":[0.9938205,0.00001612251,0.0004344978,0.0002279024,0.00005569998,0.0005070131,0.00001475674,0.00003476468,0.00488878],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1103405,"threshold_uncertainty_score":0.9999444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00584142739242807,"score_gpt":0.2431432483216551,"score_spread":0.2373018209292271,"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."}}