{"id":"W2910302863","doi":"10.5267/j.ijdns.2018.12.003","title":"Application of MADM methods as MOORA and WEDBA for ranking of FMS flexibility","year":2019,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Flexibility (engineering); Ranking (information retrieval); Computer science; Mathematics; Statistics; Information retrieval","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":[0.004033848,0.001622123,0.001726575,0.01046769,0.0009600712,0.002628993,0.001053277,0.0007891249,0.004483889],"category_scores_gemma":[0.01148356,0.000411811,0.001877744,0.006235385,0.0006561761,0.001605561,0.001482982,0.001054635,0.0004715291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001487887,"about_ca_system_score_gemma":0.001474466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004084722,"about_ca_topic_score_gemma":0.004159573,"domain_scores_codex":[0.9944811,0.002272551,0.000470056,0.0005230428,0.001973028,0.0002802286],"domain_scores_gemma":[0.9954269,0.002742898,0.0005748709,0.0002185483,0.0009382555,0.00009844396],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003546285,0.0003357334,0.01354496,0.001374626,0.0008405235,0.0001856079,0.0007048548,0.1580804,0.006724759,0.04346661,0.005308965,0.7690783],"study_design_scores_gemma":[0.00009869696,0.0006643526,0.01499087,0.0002793054,0.0002687868,0.0002857556,0.001283069,0.8989429,0.007806512,0.05618378,0.01899081,0.0002051092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04672198,0.001654864,0.9398548,0.0003481061,0.0001299563,0.0005349304,0.001004987,0.0006344182,0.009116054],"genre_scores_gemma":[0.3327766,0.0007109922,0.6620033,0.00008853463,0.00005525666,0.001025805,0.000956902,0.00009425416,0.002288286],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01046769,"threshold_uncertainty_score":0.02133328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04005007203996877,"score_gpt":0.3741401137562334,"score_spread":0.3340900417162647,"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."}}