{"id":"W3174967186","doi":"10.1210/clinem/dgab435","title":"Predicting Malignancy in Pediatric Thyroid Nodules: Early Experience With Machine Learning for Clinical Decision Support","year":2021,"lang":"en","type":"article","venue":"The Journal of Clinical Endocrinology & Metabolism","topic":"Thyroid Cancer Diagnosis and Treatment","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; Canadian Institute for Advanced Research; Hospital for Sick Children; University of Toronto","funders":"Genome Canada; Canadian Institutes of Health Research; Garron Family Cancer Centre; Rare Disease Foundation; Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Thyroid nodules; Malignancy; Thyroid; Medicine; Computer science; Medical physics; Radiology; Pathology; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01380502,0.0007646271,0.0005313587,0.001109693,0.0001741679,0.001498744,0.001317091,0.0009079795,0.00118114],"category_scores_gemma":[0.03540104,0.0002561654,0.000661763,0.0007883947,0.0006650501,0.001908635,0.0008754093,0.002940933,0.0005683451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006755727,"about_ca_system_score_gemma":0.001022445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002581236,"about_ca_topic_score_gemma":0.002271481,"domain_scores_codex":[0.9956812,0.002516125,0.0002844411,0.0004298174,0.0009559909,0.0001324589],"domain_scores_gemma":[0.9741774,0.01942105,0.0009196013,0.0009250434,0.003519445,0.00103741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004927542,0.0005536185,0.1255932,0.0003884775,0.0002019012,0.001099881,0.0009440669,0.01531271,0.00241879,0.001906102,0.007587585,0.843501],"study_design_scores_gemma":[0.0004839278,0.005736204,0.2441337,0.004120489,0.0005123717,0.01716883,0.001986802,0.5127431,0.02317082,0.02430218,0.1652485,0.0003931939],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4479244,0.07341946,0.4159236,0.04526622,0.0008730557,0.0006525292,0.0007772368,0.002107717,0.01305585],"genre_scores_gemma":[0.6397802,0.02344948,0.3313777,0.002369334,0.0009843694,0.0001817346,0.0004418602,0.000180066,0.001235161],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01380502,"threshold_uncertainty_score":0.07300878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05652470347417492,"score_gpt":0.4015455084152177,"score_spread":0.3450208049410428,"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."}}