{"id":"W2063381313","doi":"10.1158/1538-7445.am10-92","title":"Abstract 92: dbCPCO: The database of genetic predictive and prognostic factors in colorectal cancer","year":2010,"lang":"en","type":"article","venue":"Cancer Research","topic":"Colorectal Cancer Treatments and Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Newfoundland and Labrador Centre for Applied Health Research","funders":"","keywords":"Colorectal cancer; Disease; Medicine; Cancer; Personalized medicine; Oncology; Germline mutation; Germline; Database; Bioinformatics; Internal medicine; Mutation; Genetics; Biology; Gene","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":[0.003039686,0.001367615,0.003553428,0.02825354,0.0006538536,0.004661263,0.002178294,0.00162617,0.03038848],"category_scores_gemma":[0.03340879,0.0006622962,0.0009513376,0.04523715,0.0004906399,0.002658953,0.002387248,0.000928307,0.01132206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001346775,"about_ca_system_score_gemma":0.006430076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005467454,"about_ca_topic_score_gemma":0.00819857,"domain_scores_codex":[0.9960966,0.0007330849,0.002160355,0.000366861,0.0005185865,0.0001246462],"domain_scores_gemma":[0.9668071,0.01648773,0.00781216,0.002027352,0.004902975,0.001962727],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002639011,0.000150181,0.02835598,0.1916051,0.002265416,0.001587306,0.001390949,0.00125281,0.005692929,0.006339057,0.5706287,0.1880926],"study_design_scores_gemma":[0.000926237,0.0002312787,0.05364165,0.02332184,0.002095768,0.002159738,0.0006071164,0.0008132228,0.00180459,0.002134106,0.9120394,0.0002251312],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003423747,0.01420734,0.001034108,0.0004708744,0.00008588313,0.0004853579,0.9748425,0.00113921,0.004310881],"genre_scores_gemma":[0.01966923,0.02044636,0.0113482,0.000668897,0.0002014411,0.001937499,0.9437375,0.0005059203,0.001484942],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03038848,"threshold_uncertainty_score":0.1016596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06511545284470384,"score_gpt":0.4080837525134313,"score_spread":0.3429682996687275,"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."}}