{"id":"W1218083405","doi":"10.3233/ifs-131068","title":"Induced generalized Choquet aggregating operators with linguistic information and their application to multiple attribute decision making based on the intelligent computing","year":2014,"lang":"en","type":"article","venue":"Journal of Intelligent & Fuzzy Systems","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Choquet integral; Computer science; Artificial intelligence; Linguistics; Natural language processing; Fuzzy logic","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002527912,0.0008017038,0.0008181779,0.001133847,0.0005183563,0.001075754,0.0008083928,0.0005548555,0.0009251777],"category_scores_gemma":[0.004511589,0.00023916,0.001191612,0.001715824,0.0008613035,0.00165109,0.001041952,0.001017987,0.0001054364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006061838,"about_ca_system_score_gemma":0.0007871088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001307841,"about_ca_topic_score_gemma":0.0009096612,"domain_scores_codex":[0.997889,0.0009213485,0.000145982,0.0002470653,0.0007034123,0.00009325425],"domain_scores_gemma":[0.9986672,0.0006832195,0.0001445856,0.0001036115,0.0003609247,0.00004046224],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000143477,0.00008947514,0.001182972,0.0005286457,0.000313338,0.0003976159,0.0008038218,0.3540352,0.01723955,0.4340014,0.001578917,0.1896857],"study_design_scores_gemma":[0.00001232432,0.00008626761,0.0002911754,0.00002304157,0.00004360309,0.00008571186,0.00005314565,0.8912676,0.002127313,0.1040295,0.001944059,0.00003620861],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009880229,0.0003856179,0.9881346,0.00007226899,0.00004831902,0.00002567129,0.0000142269,0.00004157034,0.001397433],"genre_scores_gemma":[0.4525451,0.000926907,0.5445022,0.0001242736,0.0001811319,0.0001942015,0.00007338377,0.00003767744,0.00141502],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002527912,"threshold_uncertainty_score":0.01336902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02103302846130191,"score_gpt":0.2556542049307103,"score_spread":0.2346211764694084,"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."}}