{"id":"W4385568192","doi":"10.1101/2023.08.04.551970","title":"Machine learning-based meta-analysis of colorectal cancer and inflammatory bowel disease","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genetic factors in colorectal cancer","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Colorectal cancer; Disease; Inflammatory bowel disease; Medicine; Cancer; Univariate; Meta-analysis; Bioinformatics; Oncology; Computational biology; Internal medicine; Biology; Multivariate statistics; Machine learning; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.02165793,0.001544678,0.003604449,0.004769909,0.0007752322,0.003014037,0.001587984,0.001071119,0.003842535],"category_scores_gemma":[0.04360452,0.0005766774,0.013369,0.00553628,0.0004788666,0.001120092,0.001454646,0.002681189,0.0004823878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009494803,"about_ca_system_score_gemma":0.002061493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004865759,"about_ca_topic_score_gemma":0.005931879,"domain_scores_codex":[0.9821219,0.01297564,0.000925156,0.002483934,0.001170322,0.0003230274],"domain_scores_gemma":[0.9557051,0.03667729,0.002070868,0.003969719,0.0009492877,0.0006276982],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.005708426,0.0001830118,0.3066344,0.01081495,0.5093002,0.0007982132,0.0001084982,0.06797899,0.003276668,0.003959808,0.01415535,0.07708153],"study_design_scores_gemma":[0.001521214,0.001559583,0.1827268,0.002973127,0.4347517,0.001646958,0.0001769164,0.2831178,0.005030231,0.0544873,0.03171426,0.0002941664],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.3021507,0.3706077,0.2557461,0.01732105,0.003295781,0.0005487492,0.04214769,0.003426479,0.004755711],"genre_scores_gemma":[0.946852,0.01349052,0.0292167,0.001067001,0.0008099768,0.0002307505,0.00708386,0.000352021,0.0008970844],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02165793,"threshold_uncertainty_score":0.1145394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03371734010005874,"score_gpt":0.2675576862734482,"score_spread":0.2338403461733894,"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."}}