{"id":"W2887700403","doi":"10.1016/j.neo.2018.07.007","title":"Characterizing Microsatellite Instability and Chromosome Instability in Interval Colorectal Cancers","year":2018,"lang":"en","type":"article","venue":"Neoplasia","topic":"Genetic factors in colorectal cancer","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"CancerCare Manitoba; Research Institute in Oncology and Hematology; University of Manitoba","funders":"Canadian Institutes of Health Research; Strong; CancerCare Manitoba Foundation","keywords":"Microsatellite instability; MLH1; MSH2; PMS2; MSH6; Chromosome instability; Population; Oncology; Biology; Colorectal cancer; Internal medicine; Genetics; Medicine; Cancer research; Chromosome; Cancer; DNA mismatch repair; Microsatellite; Gene; Allele","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003428461,0.000242861,0.0004504097,0.0001177326,0.0000713933,0.00003182776,0.000110992,0.0001832415,0.0004237689],"category_scores_gemma":[0.0002254162,0.0002298977,0.00006523707,0.0003333704,0.0006546786,0.000124552,0.0001401454,0.0003603247,0.00003460722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008824923,"about_ca_system_score_gemma":0.0003870951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005630257,"about_ca_topic_score_gemma":0.003597062,"domain_scores_codex":[0.9982417,0.00008236739,0.0004199642,0.0005919886,0.0002244633,0.0004395285],"domain_scores_gemma":[0.9991685,0.00009225532,0.00008557815,0.0003377827,0.0001198819,0.0001959814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001053664,0.00008821656,0.6801615,0.0001537966,0.0000229671,0.00001976806,0.003426747,2.890872e-7,0.2998424,0.000008355218,0.0000341836,0.015188],"study_design_scores_gemma":[0.001301481,0.0009620495,0.8661691,0.0001295744,0.00002017876,0.0001039783,0.0002462474,0.0001319547,0.1262271,0.00005588485,0.004452436,0.0002000081],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949213,0.000219735,0.000005196416,0.0003439457,0.0007479464,0.0006426317,0.00003025298,0.00006860684,0.003020362],"genre_scores_gemma":[0.9984846,0.00006209629,0.0006632829,0.0004319225,0.00022408,0.000051334,0.00001398675,0.00002831157,0.00004044612],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1860076,"threshold_uncertainty_score":0.9374957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0162360322211807,"score_gpt":0.2730543815106498,"score_spread":0.2568183492894691,"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."}}