{"id":"W2999737027","doi":"10.1016/j.cmpb.2020.105315","title":"A reliable time-series method for predicting arthritic disease outcomes: New step from regression toward a nonlinear artificial intelligence method","year":2020,"lang":"en","type":"article","venue":"Computer Methods and Programs in Biomedicine","topic":"Rheumatoid Arthritis Research and Therapies","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre Hospitalier de l’Université de Montréal; Université de Montréal","funders":"","keywords":"Series (stratigraphy); Computer science; Artificial intelligence; Machine learning; Regression; Time series; Regression analysis; Nonlinear system; Nonlinear regression; Data mining; Statistics; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001961049,0.0003853114,0.001101779,0.0002137399,0.000130972,0.0001191202,0.0002196324,0.000148798,0.00008069845],"category_scores_gemma":[0.0007959884,0.0002760845,0.0001820717,0.0006113045,0.0002237475,0.0001781293,0.0002178646,0.0004168302,0.00000726549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003055247,"about_ca_system_score_gemma":0.000195334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002429627,"about_ca_topic_score_gemma":0.000008632412,"domain_scores_codex":[0.9968028,0.0005006529,0.0008543783,0.0008340984,0.0004143009,0.0005937786],"domain_scores_gemma":[0.9971192,0.00114846,0.0001537485,0.0003579138,0.0001503699,0.00107024],"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":[0.001738272,0.0001869434,0.003852461,0.00028883,0.0001335906,0.00008715006,0.002539466,0.00000577926,0.001591929,0.0002467508,0.0003441789,0.9889846],"study_design_scores_gemma":[0.005004714,0.006496133,0.001809919,0.003812688,0.0001267198,0.00007163439,0.001544421,0.8536913,0.002652904,0.02678568,0.09731564,0.0006882675],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003737611,0.009264038,0.9660223,0.01880592,0.0003015947,0.00163121,0.00003784967,0.000184303,0.00001518562],"genre_scores_gemma":[0.0009165692,0.001834028,0.9945394,0.001273833,0.0009840099,0.0001275996,0.0002122387,0.0000537071,0.00005864352],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9882964,"threshold_uncertainty_score":0.9999691,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09234682616529696,"score_gpt":0.4120229177593929,"score_spread":0.3196760915940959,"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."}}