{"id":"W2902029463","doi":"10.1016/s0140-6736(18)32170-6","title":"Artificial intelligence can augment global pathology initiatives – Authors' reply","year":2018,"lang":"en","type":"letter","venue":"The Lancet","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Augment; Computer science; Medicine","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":[0.006363136,0.0008181316,0.001730493,0.001126113,0.003937288,0.006951191,0.00226933,0.08870944,0.009494458],"category_scores_gemma":[0.05399505,0.00104616,0.001434765,0.0007560275,0.005902062,0.004989116,0.003998971,0.0651433,0.007743463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004138802,"about_ca_system_score_gemma":0.005548988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004023525,"about_ca_topic_score_gemma":0.005895756,"domain_scores_codex":[0.9933994,0.001856862,0.0007099941,0.0009520838,0.002168862,0.0009128039],"domain_scores_gemma":[0.9645405,0.02184702,0.002417434,0.001038713,0.006107566,0.004048746],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002794347,0.00001148887,0.0002768686,0.00005234806,0.00001949191,0.0003785187,0.0001272458,0.0000324644,0.00006406403,0.001937544,0.9934609,0.003611186],"study_design_scores_gemma":[0.0001326524,0.00004506441,0.0007475641,0.0003948509,0.00004674214,0.0006771401,0.0006442955,0.0001850871,0.0001886036,0.01116628,0.9856801,0.00009158818],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.00006120369,0.0008635748,0.00003050655,0.9830118,0.01556746,0.000003297215,0.00002289463,0.000009582994,0.0004296219],"genre_scores_gemma":[0.001140915,0.0005382198,0.00006266699,0.9694519,0.02698269,0.00001683851,0.00001337028,0.00001073035,0.001782677],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.08870944,"threshold_uncertainty_score":0.03365189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04965424481006546,"score_gpt":0.3508445497220379,"score_spread":0.3011903049119724,"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."}}