{"id":"W2990078743","doi":"10.3390/cancers11121907","title":"Proteogenomics of Colorectal Cancer Liver Metastases: Complementing Precision Oncology with Phenotypic Data","year":2019,"lang":"en","type":"article","venue":"Cancers","topic":"Colorectal Cancer Treatments and Studies","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Jewish General Hospital","funders":"Genome Canada","keywords":"KRAS; Colorectal cancer; Proteogenomics; Medicine; Phenotype; Cancer research; Internal medicine; Oncology; Digital polymerase chain reaction; Cancer; Bioinformatics; Biology; Transcriptome; Gene; Genetics; Gene expression; Polymerase chain reaction","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":[0.0001484614,0.0001559158,0.0004888618,0.0000567123,0.00006024713,0.000006653782,0.0001639858,0.00003912266,0.0007664654],"category_scores_gemma":[0.00001836989,0.0001099269,0.00004318899,0.0001709279,0.0001106947,0.0000877603,0.0001900371,0.0001044933,0.00001118717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001449614,"about_ca_system_score_gemma":0.001231038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002211123,"about_ca_topic_score_gemma":0.002660078,"domain_scores_codex":[0.9988981,0.00003051043,0.0002341511,0.0003842451,0.0002131856,0.0002397425],"domain_scores_gemma":[0.9991693,0.0000710719,0.0001894466,0.0003657365,0.0001362209,0.00006825217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.02889712,0.0005764767,0.4666899,0.001677493,0.007442438,0.0001800558,0.007360965,0.002782116,0.03872318,0.0005220657,0.009253512,0.4358947],"study_design_scores_gemma":[0.04325517,0.02794113,0.3098754,0.002387594,0.005989733,0.0001788546,0.01002791,0.02168799,0.05735741,0.00007845108,0.5194938,0.001726529],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9897956,0.002979863,0.00005304387,0.0001154172,0.0002181727,0.001480682,0.0003852424,0.00002166783,0.004950294],"genre_scores_gemma":[0.9954206,0.0006292578,0.003136538,0.0001229644,0.00006791096,0.0001394197,0.0001301386,0.00002234521,0.0003308669],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5102403,"threshold_uncertainty_score":0.8392259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05608268828848995,"score_gpt":0.3408768291329841,"score_spread":0.2847941408444942,"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."}}