{"id":"W2360393060","doi":"10.1016/j.compmedimag.2016.05.001","title":"WITHDRAWN: Adaptive Swarm Balancing Algorithms for rare-event prediction in imbalanced healthcare data","year":2016,"lang":"en","type":"article","venue":"Computerized Medical Imaging and Graphics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lakehead University","funders":"","keywords":"Computer science; Event (particle physics); Rare events; Event data; Swarm behaviour; Algorithm; Artificial intelligence; Data mining; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":{"nature":"Retraction","reason":"Date of Article and/or Notice Unknown;Notice - Limited or No Information;Removed;","date":"5/10/2016 0:00","openalex_flagged":false},"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001680544,0.0002184166,0.0003805961,0.0001801377,0.0001463949,0.00008879779,0.000964567,0.0001229152,0.000001574074],"category_scores_gemma":[0.0001814727,0.0001541119,0.00005834884,0.0003340002,0.0001727736,0.0005176055,0.0006328195,0.0002626736,7.157879e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003666693,"about_ca_system_score_gemma":0.0002072587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004386369,"about_ca_topic_score_gemma":0.00001512458,"domain_scores_codex":[0.9975718,0.0002176781,0.000437486,0.0008645514,0.0004282253,0.0004802611],"domain_scores_gemma":[0.9981845,0.000451769,0.0001207638,0.0007585759,0.0001075823,0.0003768038],"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":[0.00004123091,0.00006048497,0.001033654,0.00006378864,0.00002088457,0.00004794179,0.0003002014,7.953731e-7,0.0001694214,0.03141507,0.001464978,0.9653816],"study_design_scores_gemma":[0.003044478,0.0001091189,0.002390525,0.0007716043,0.000009951002,0.0001017287,0.00001220681,0.9339757,0.00006754637,0.05636827,0.002891542,0.0002573658],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0008037099,0.00102437,0.9802582,0.0163497,0.0009788427,0.000341819,0.00006052803,0.0001662892,0.00001659592],"genre_scores_gemma":[0.2322416,0.0006567342,0.7636165,0.002883606,0.0004531575,0.00005674363,0.0000374196,0.00002465285,0.00002957438],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9651242,"threshold_uncertainty_score":0.6284499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03440100624848556,"score_gpt":0.3204346604410896,"score_spread":0.2860336541926041,"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."}}