{"id":"W4401069860","doi":"10.1109/access.2024.3434617","title":"Predictive Analytics: An Optimization Perspective","year":2024,"lang":"en","type":"article","venue":"IEEE Access","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Concordia University","funders":"","keywords":"Computer science; Predictive analytics; Perspective (graphical); Machine learning; Analytics; Data analysis; Artificial intelligence; Data science; Artificial neural network; Data mining; Mathematical optimization; Mathematics","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":[0.004138879,0.002186366,0.002215922,0.002419796,0.0005620602,0.004841061,0.002230355,0.002435801,0.002599338],"category_scores_gemma":[0.00885386,0.0008197465,0.001376833,0.003241323,0.004373543,0.006439408,0.00175068,0.006090786,0.001053217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002453017,"about_ca_system_score_gemma":0.001664862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002860546,"about_ca_topic_score_gemma":0.001216991,"domain_scores_codex":[0.996311,0.0014916,0.0001860546,0.0005174822,0.001344752,0.00014902],"domain_scores_gemma":[0.9939201,0.004926019,0.0002448759,0.000238018,0.0005545456,0.0001164792],"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":[0.00002790624,0.0000479091,0.0002743329,0.0004106303,0.00009210638,0.00008009869,0.00005600841,0.08770557,0.0002761904,0.8609858,0.007188232,0.04285517],"study_design_scores_gemma":[0.00001116607,0.00004316635,0.0001806578,0.0001932688,0.00002984493,0.00005353369,0.00003523003,0.1646174,0.0002993057,0.8113995,0.0231081,0.00002894524],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00160907,0.04879777,0.9075935,0.01856901,0.0008823103,0.00004231756,0.0002963021,0.0001818879,0.02202772],"genre_scores_gemma":[0.3853558,0.2235947,0.3456092,0.008732702,0.01987242,0.000557268,0.0009001392,0.0004286093,0.01494918],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004841061,"threshold_uncertainty_score":0.02188873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03430678945445772,"score_gpt":0.3439158340500761,"score_spread":0.3096090445956184,"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."}}