{"id":"W3137049914","doi":"10.1002/gcc.22949","title":"Histology‐based molecular profiling improves mutation detection for advanced thyroid cancer","year":2021,"lang":"en","type":"article","venue":"Genes Chromosomes and Cancer","topic":"Thyroid Cancer Diagnosis and Treatment","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health Services; University of Calgary","funders":"","keywords":"Neuroblastoma RAS viral oncogene homolog; Microsatellite instability; Pathology; Thyroid cancer; Cancer research; Biology; Genetic heterogeneity; Tumour heterogeneity; Molecular pathology; HRAS; Thyroid; Cancer; Mutation; Medicine; Gene; KRAS; Genetics; Allele; Phenotype; Microsatellite","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":[0.0004645802,0.0002611012,0.000288901,0.001061886,0.0001734917,0.0004519525,0.0002076606,0.0002054145,0.001174237],"category_scores_gemma":[0.0007617301,0.0001482758,0.0001794573,0.0003435847,0.000174867,0.0001908552,0.0002623531,0.000194384,0.0002951597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002401487,"about_ca_system_score_gemma":0.0001840599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001397494,"about_ca_topic_score_gemma":0.003384258,"domain_scores_codex":[0.999818,0.00004438941,0.00001671536,0.00004445076,0.00005468162,0.00002179262],"domain_scores_gemma":[0.9997531,0.00007101428,0.0000602799,0.00003296489,0.00005534761,0.00002731702],"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":[0.0005195554,0.00003507606,0.2087695,0.0001581285,0.0001010318,0.0007521036,0.0001393004,0.001404596,0.7381841,0.0002036305,0.0002795113,0.04945362],"study_design_scores_gemma":[0.00002217495,0.0003449274,0.829627,0.00002756532,0.0002013859,0.004905402,0.0002705923,0.008685142,0.1493921,0.0005517585,0.005944501,0.00002755131],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9852056,0.002664368,0.009786051,0.0000954729,0.00001433272,0.00005665896,0.000599607,0.0001613966,0.001416561],"genre_scores_gemma":[0.9925327,0.0006505026,0.005888675,0.00003701382,0.000007752534,0.00001581918,0.0003704153,0.00002135847,0.0004758033],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001397494,"threshold_uncertainty_score":0.003928244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01187512747596092,"score_gpt":0.2922042783212894,"score_spread":0.2803291508453284,"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."}}