{"id":"W3012311931","doi":"10.1097/cm9.0000000000000714","title":"Artificial intelligence in inflammatory bowel disease: current status and opportunities","year":2020,"lang":"en","type":"article","venue":"Chinese Medical Journal","topic":"Inflammatory Bowel Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Fundamental Research Funds for the Central Universities","keywords":"Medicine; Inflammatory bowel disease; Ulcerative colitis; Disease; Crohn's disease; Health care; Internal medicine","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":[0.0003309785,0.0001710058,0.0001224606,0.00005581763,0.00007818406,0.00006296651,0.0002079812,0.00008458672,0.000201263],"category_scores_gemma":[0.001161584,0.0001375531,0.00007223702,0.00004427406,0.0002171544,0.00001232072,0.0001751241,0.0004072358,0.00001054443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001599157,"about_ca_system_score_gemma":0.000672685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.889882e-7,"about_ca_topic_score_gemma":0.000008201045,"domain_scores_codex":[0.9985031,0.0001314107,0.000419773,0.0002253087,0.000419707,0.0003006888],"domain_scores_gemma":[0.9981316,0.0000166411,0.000085195,0.0001208082,0.00005931788,0.001586384],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001887258,0.0002655805,0.6779241,0.0003799229,0.00006970236,0.006387781,0.0009164595,0.0001843355,0.001670522,0.001779775,0.001976978,0.3065576],"study_design_scores_gemma":[0.000644603,0.0001388232,0.966485,0.0001988338,0.00003323037,0.0001099174,0.0003445033,0.007793183,0.0001483161,0.004805982,0.0187069,0.0005907554],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9916286,0.004211127,0.001350925,0.002310602,0.0002991606,0.00009083142,0.00001376705,0.00001083353,0.00008415835],"genre_scores_gemma":[0.9940349,0.003546682,0.0000306519,0.001073017,0.001253221,0.000007462835,0.00002877672,0.00001758717,0.000007637761],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3059669,"threshold_uncertainty_score":0.5609252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02449462855901876,"score_gpt":0.2889921048907333,"score_spread":0.2644974763317146,"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."}}