{"id":"W4387613748","doi":"10.1016/j.clcc.2023.10.004","title":"Optimizing Fecal Occult Blood Test (FOBT) Colorectal Cancer Screening Using Gut Bacteriome as a Biomarker","year":2023,"lang":"en","type":"article","venue":"Clinical Colorectal Cancer","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"Canadian Institutes of Health Research","keywords":"Fecal occult blood; Colorectal cancer; Medicine; Biomarker; Oncology; Internal medicine; Colorectal cancer screening; Feces; Colonoscopy; Cancer; Biology; Genetics","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":[0.0006239896,0.0005701684,0.0008035765,0.000901014,0.000244329,0.00105765,0.0002476089,0.0006007679,0.0006192001],"category_scores_gemma":[0.002025885,0.0001889691,0.0002945042,0.0006811935,0.0001564892,0.0003508809,0.0003779329,0.0004288688,0.0003269796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003086928,"about_ca_system_score_gemma":0.0007392097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001635942,"about_ca_topic_score_gemma":0.002977411,"domain_scores_codex":[0.9993657,0.0002140796,0.00003608227,0.0001117306,0.0001991528,0.00007318868],"domain_scores_gemma":[0.9994941,0.0001531658,0.000102116,0.0000205076,0.0001707194,0.00005943384],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001839965,0.0009399106,0.3423814,0.0007308819,0.0002432156,0.0004943247,0.0001759209,0.003344856,0.3813563,0.0005756611,0.003929072,0.2639885],"study_design_scores_gemma":[0.0001805115,0.006699651,0.4963266,0.0005584313,0.00127195,0.002731076,0.001125174,0.05409833,0.4085327,0.002350964,0.0260096,0.0001149491],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9424316,0.01577955,0.03226183,0.002683259,0.0003640141,0.0002375073,0.0009772665,0.00053298,0.004732033],"genre_scores_gemma":[0.9673894,0.002812943,0.02681578,0.0009827531,0.0001358892,0.00008365974,0.000426527,0.00003675067,0.001316277],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001635942,"threshold_uncertainty_score":0.003300011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07118089293178677,"score_gpt":0.4059329058284157,"score_spread":0.3347520128966289,"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."}}