{"id":"W4320803774","doi":"10.3390/mol2net-08-13815","title":"Application of Multicriteria Analysis to Increase the Quality of Cuban Tobacco","year":2022,"lang":"en","type":"article","venue":"Proceedings of MOL2NET'22, Conference on Molecular, Biomedical & Computational Sciences and Engineering, 8th ed. - MOL2NET: FROM MOLECULES TO NETWORKS","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Quality (philosophy); Computer science; Pleasure; Habit; Tobacco industry; Risk analysis (engineering); Degree (music); Operations research; Mathematics; Psychology; Medicine","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":[0.0006278052,0.000368177,0.0004226952,0.000883923,0.0003030211,0.0007641631,0.0004385223,0.0003432419,0.0008086513],"category_scores_gemma":[0.001445354,0.000195336,0.0005587573,0.0006067433,0.0003111568,0.0003420873,0.0004862334,0.0003284699,0.00009674153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001712965,"about_ca_system_score_gemma":0.0007018399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01953909,"about_ca_topic_score_gemma":0.009683811,"domain_scores_codex":[0.9997728,0.0000694456,0.00001077794,0.0000621239,0.00005848208,0.00002630785],"domain_scores_gemma":[0.9995345,0.0001691103,0.00006969973,0.00005097051,0.0001610709,0.00001464975],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003048571,0.0001065417,0.01000212,0.0001174916,0.00009232756,0.000139131,0.0002093413,0.8504415,0.03983853,0.007396679,0.0005947981,0.09075672],"study_design_scores_gemma":[0.000003124095,0.0000351138,0.001530901,0.000002655616,0.00001051845,0.00001580451,0.00002153445,0.9925491,0.004704768,0.0007234209,0.000392437,0.00001066814],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.673376,0.000605538,0.3175305,0.0004217056,0.00006523919,0.0001180209,0.0002589879,0.0006464269,0.006977577],"genre_scores_gemma":[0.9558037,0.0001026309,0.04294357,0.00002183234,0.000005101462,0.00002974333,0.00007716173,0.0000433707,0.0009729885],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01953909,"threshold_uncertainty_score":0.03885072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01219741649000366,"score_gpt":0.264771504719865,"score_spread":0.2525740882298614,"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."}}