{"id":"W2399886942","doi":"","title":"Clustering of Products to Identify Optimal Inventory Prediction Models.","year":2011,"lang":"en","type":"article","venue":"Indian International Conference on Artificial Intelligence","topic":"Statistical and Computational Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Cluster analysis; Computer science; Data mining; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002409414,0.0001508631,0.0001423282,0.0003291464,0.0000747258,0.0001182056,0.001089195,0.00005525049,0.0001626236],"category_scores_gemma":[0.000144118,0.0001570668,0.00004965668,0.0003181138,0.00007379906,0.0005105843,0.0002432451,0.0001576434,0.0001999076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006643185,"about_ca_system_score_gemma":0.0001299714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001180745,"about_ca_topic_score_gemma":0.00002076255,"domain_scores_codex":[0.9981598,0.00004388811,0.0005360361,0.000485066,0.0005555514,0.0002196606],"domain_scores_gemma":[0.998743,0.00004815296,0.0001367854,0.0002795119,0.0006557963,0.0001367353],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006621832,0.0001406893,0.00003033864,0.00001025106,0.00002168345,0.00001468574,0.003958254,0.04035263,0.00100909,0.8904043,0.00003303399,0.06395879],"study_design_scores_gemma":[0.00001746139,0.0001452166,0.0003749937,0.0000771085,0.000002377031,0.000006551862,0.0001733834,0.7531211,0.01080315,0.2351444,0.00001023271,0.0001240361],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02342448,0.000004889238,0.9675503,0.0006108811,0.001194409,0.0001787414,0.00002774085,0.00007587999,0.006932639],"genre_scores_gemma":[0.9069993,0.000005647943,0.09259889,0.000194398,0.0001042553,0.00002879545,0.000007845114,0.000008048532,0.00005275791],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8835749,"threshold_uncertainty_score":0.6404996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2398035938578342,"score_gpt":0.3504457422213326,"score_spread":0.1106421483634984,"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."}}