{"id":"W2071294636","doi":"10.4236/ti.2012.32010","title":"Research on Stratified Cluster Evaluation of Enterprise Green Technology Innovation Based on the Rough Set","year":2012,"lang":"en","type":"article","venue":"Technology and Investment","topic":"Environmental Sustainability in Business","field":"Business, Management and Accounting","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bottleneck; Rough set; Ambiguity; Computer science; Cluster analysis; Index (typography); Set (abstract data type); Empirical research; Objectivity (philosophy); Data mining; Knowledge management; Industrial engineering; Operations research; Artificial intelligence; Mathematics; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.004986713,0.0004923707,0.001177717,0.003947866,0.0009173113,0.002673338,0.0008203232,0.0004944199,0.0007003343],"category_scores_gemma":[0.01553366,0.0002629153,0.001279396,0.002785274,0.001186377,0.002957189,0.0008828486,0.0005717637,0.00008760427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00347255,"about_ca_system_score_gemma":0.002018719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005778348,"about_ca_topic_score_gemma":0.003604567,"domain_scores_codex":[0.9941025,0.002487786,0.0003409403,0.0004376016,0.002346334,0.0002847726],"domain_scores_gemma":[0.9925725,0.003968615,0.0006196452,0.0004300809,0.002241679,0.0001674281],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003302087,0.0001968091,0.02153571,0.0007363975,0.000807851,0.0001804491,0.001754727,0.5121362,0.00642128,0.1611319,0.002078958,0.2926895],"study_design_scores_gemma":[0.00003091857,0.0001926321,0.01001057,0.00008285412,0.0002070977,0.00007293771,0.0005198083,0.9334181,0.004366322,0.04880928,0.002200584,0.00008881594],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1759665,0.001085215,0.8155088,0.0004372046,0.00005516934,0.0002528291,0.0001005095,0.0001728577,0.006420895],"genre_scores_gemma":[0.8812384,0.0004721519,0.1173341,0.00004004476,0.0000303638,0.0001713273,0.0001274761,0.00001921565,0.0005669761],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005778348,"threshold_uncertainty_score":0.02637261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07338900404856924,"score_gpt":0.3255207047657789,"score_spread":0.2521317007172097,"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."}}