{"id":"W1597434037","doi":"10.1007/978-3-540-72432-2_83","title":"A Fuzzy Model for Supplier Selection and Development","year":2007,"lang":"en","type":"book-chapter","venue":"Advances in soft computing","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Selection (genetic algorithm); Fuzzy logic; Base (topology); Computer science; Value (mathematics); Operations research; Mathematical optimization; Engineering; Artificial intelligence; Mathematics; Machine learning","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":[0.001042165,0.0009502554,0.0009660959,0.001244558,0.0008523084,0.002145932,0.002445673,0.002658354,0.01232962],"category_scores_gemma":[0.002218908,0.0004946386,0.001279847,0.002195928,0.0007416179,0.002825301,0.0008237424,0.00147911,0.001962894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002053575,"about_ca_system_score_gemma":0.001615568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01475659,"about_ca_topic_score_gemma":0.01272956,"domain_scores_codex":[0.9995165,0.0001807005,0.00002450083,0.000084603,0.0001470286,0.00004664328],"domain_scores_gemma":[0.9994276,0.0003694676,0.0000370766,0.00003262812,0.000102602,0.00003070101],"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":[0.00005612877,0.00007334933,0.0003277374,0.0001245032,0.000064609,0.0002138253,0.0001480927,0.6197976,0.0008147819,0.3157065,0.006583076,0.05608976],"study_design_scores_gemma":[0.00001333369,0.00002440866,0.0001029533,0.00002131125,0.00001775422,0.00006022242,0.00002842162,0.8898619,0.000143226,0.1052101,0.004498844,0.00001746134],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008931843,0.0009902203,0.9551741,0.001236026,0.0001978055,0.00007643439,0.0005200741,0.0002460274,0.03262759],"genre_scores_gemma":[0.5245796,0.003143657,0.3922632,0.0004510522,0.0002650158,0.0006599525,0.0008803051,0.0001538325,0.07760343],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01475659,"threshold_uncertainty_score":0.04124665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1867025491514293,"score_gpt":0.4374200214677522,"score_spread":0.2507174723163229,"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."}}