{"id":"W4383906866","doi":"10.1186/s12885-023-10848-9","title":"Identifying important microbial and genomic biomarkers for differentiating right- versus left-sided colorectal cancer using random forest models","year":2023,"lang":"en","type":"article","venue":"BMC Cancer","topic":"Ferroptosis and cancer prognosis","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"Massey University","keywords":"Surgical oncology; Colorectal cancer; Medicine; Random forest; Computational biology; Internal medicine; Cancer; Oncology; Bioinformatics; Biology; Computer science; Artificial intelligence","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":[0.005956267,0.001708843,0.001439406,0.00173845,0.000641616,0.0009999855,0.001082199,0.001290999,0.001755077],"category_scores_gemma":[0.006189757,0.0003647067,0.00318886,0.0007413582,0.0005395704,0.0006880511,0.0006060523,0.001518197,0.0008290451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006994472,"about_ca_system_score_gemma":0.001125495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007159914,"about_ca_topic_score_gemma":0.006162613,"domain_scores_codex":[0.9986801,0.0005914982,0.00006796474,0.0004011986,0.00008448715,0.0001747239],"domain_scores_gemma":[0.9956601,0.003355125,0.0002817113,0.0001393936,0.0003932916,0.0001702788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002980055,0.0007394332,0.1831295,0.0004886111,0.001542641,0.0005254845,0.0002125913,0.6650928,0.008175788,0.001966554,0.007897923,0.1272486],"study_design_scores_gemma":[0.00007122915,0.0001944648,0.006565849,0.0000387551,0.0001767479,0.000103565,0.00003400128,0.9888294,0.0008390537,0.002539162,0.0005812032,0.0000265544],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6633785,0.003399764,0.3205319,0.001648375,0.0003012535,0.0003886676,0.005976573,0.002415929,0.001959046],"genre_scores_gemma":[0.9198192,0.0003830614,0.070324,0.0004319915,0.0001566412,0.0003137765,0.0073881,0.0001225688,0.001060538],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007159914,"threshold_uncertainty_score":0.0315001,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08097500346782348,"score_gpt":0.3372451885063991,"score_spread":0.2562701850385756,"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."}}