{"id":"W3021493143","doi":"10.1136/gutjnl-2019-320466","title":"Machine learning in GI endoscopy: practical guidance in how to interpret a novel field","year":2020,"lang":"en","type":"review","venue":"Gut","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":123,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver General Hospital; University of British Columbia","funders":"","keywords":"Terminology; Novelty; Computer science; Quality (philosophy); Artificial intelligence; Relevance (law); Field (mathematics); Multidisciplinary approach; Machine learning; Data science; Psychology","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":[0.07012001,0.001443095,0.003804444,0.008970304,0.001295637,0.006900397,0.003607774,0.006736465,0.006528376],"category_scores_gemma":[0.2154744,0.001016404,0.00292756,0.006848972,0.005134915,0.01231773,0.002891893,0.009178616,0.006490639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003149522,"about_ca_system_score_gemma":0.01233817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002341167,"about_ca_topic_score_gemma":0.004352192,"domain_scores_codex":[0.9601213,0.01985957,0.0108511,0.001258058,0.007515178,0.0003948498],"domain_scores_gemma":[0.7743708,0.1715011,0.01004081,0.006779951,0.03586498,0.001442343],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002035939,0.00006400431,0.0007796341,0.08731094,0.0005470542,0.0005547237,0.001660003,0.0005075433,0.001201462,0.03642116,0.2740956,0.5966542],"study_design_scores_gemma":[0.00008080841,0.0001413507,0.00105448,0.09059344,0.0003498015,0.001097656,0.000658687,0.0004074845,0.0004715165,0.0426849,0.8623483,0.0001115595],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002911248,0.8589104,0.02468789,0.09453715,0.01555054,0.0007986958,0.0003469011,0.0002355645,0.004641724],"genre_scores_gemma":[0.004345638,0.8382875,0.09093672,0.04914312,0.01188577,0.001657715,0.0004399983,0.0002242041,0.003079399],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.07012001,"threshold_uncertainty_score":0.3708345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06118998529213859,"score_gpt":0.3839047253643207,"score_spread":0.3227147400721821,"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."}}