{"id":"W4386695628","doi":"10.3389/fendo.2023.1220617","title":"A clinically useful and biologically informative genomic classifier for papillary thyroid cancer","year":2023,"lang":"en","type":"article","venue":"Frontiers in Endocrinology","topic":"Thyroid Cancer Diagnosis and Treatment","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health Services; University of Calgary","funders":"","keywords":"Thyroid cancer; Computational biology; Papillary thyroid cancer; Risk stratification; Classifier (UML); Medicine; Thyroid; Oncology; Bioinformatics; Internal medicine; Biology; Artificial intelligence; Computer science","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":[0.0005672787,0.0003226115,0.000395082,0.001059755,0.0002925489,0.0006764608,0.0002448231,0.0004486335,0.0007416779],"category_scores_gemma":[0.003299307,0.00008906343,0.0002686224,0.0005377231,0.0001842785,0.0002386948,0.0002939395,0.0003857866,0.0003752311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004622639,"about_ca_system_score_gemma":0.0006682822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002434003,"about_ca_topic_score_gemma":0.002885606,"domain_scores_codex":[0.9997194,0.00006445697,0.00002793302,0.0000743155,0.00007476227,0.00003914031],"domain_scores_gemma":[0.9993011,0.0004091333,0.00006399563,0.00004725903,0.0001503363,0.00002817555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006081542,0.0002506271,0.3271552,0.0001851948,0.0001446243,0.0006967835,0.0001331859,0.04911812,0.05429656,0.002379991,0.008548304,0.5564833],"study_design_scores_gemma":[0.0001227883,0.0005066802,0.1919309,0.0001006586,0.0003670136,0.002313107,0.0002950119,0.7368854,0.04114711,0.01542366,0.01083112,0.00007649734],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7838566,0.001606281,0.2016776,0.001294843,0.000100336,0.0002269867,0.006260708,0.001600873,0.003375842],"genre_scores_gemma":[0.9309236,0.000179957,0.06451039,0.0001360568,0.00004954485,0.00007831017,0.00353844,0.00003005927,0.0005536143],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002434003,"threshold_uncertainty_score":0.004839718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03538110803075489,"score_gpt":0.3257013499275219,"score_spread":0.290320241896767,"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."}}