{"id":"W2997449172","doi":"10.1148/radiol.2019192515","title":"Assessing Radiology Research on Artificial Intelligence: A Brief Guide for Authors, Reviewers, and Readers—From the <i>Radiology</i> Editorial Board","year":2019,"lang":"en","type":"editorial","venue":"Radiology","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":334,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Cancer Research UK","keywords":"Medicine; General hospital; Library science; Radiology; Family medicine; 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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.05667542,0.00515476,0.007724416,0.01829502,0.004764352,0.02835901,0.005754553,0.01576304,0.01726734],"category_scores_gemma":[0.208878,0.002394049,0.00321089,0.006496069,0.004859607,0.01216445,0.005073385,0.02061422,0.02684028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004663031,"about_ca_system_score_gemma":0.01605093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001871276,"about_ca_topic_score_gemma":0.006795369,"domain_scores_codex":[0.9403384,0.01536936,0.01654514,0.002348832,0.02411739,0.00128087],"domain_scores_gemma":[0.5982085,0.1441947,0.02730609,0.007675415,0.1951922,0.02742301],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002266516,0.00001133144,0.00003844177,0.0005073833,0.00001473973,0.00002788748,0.00003295115,0.00001250036,0.00004428062,0.0001369835,0.9841424,0.01500844],"study_design_scores_gemma":[0.00008880431,0.00005225018,0.0003478734,0.003631566,0.00007218837,0.0002472123,0.0001604047,0.0001508548,0.00008350368,0.002097578,0.9930012,0.00006658166],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00003962314,0.04418615,0.001112166,0.08314052,0.8691546,0.000235355,0.0001742208,0.0002744584,0.001682906],"genre_scores_gemma":[0.0003982347,0.03358465,0.00271843,0.05512147,0.9010578,0.0004329674,0.0002242047,0.0002649123,0.006197375],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.9433246,"threshold_uncertainty_score":0.2997319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07186118850790842,"score_gpt":0.4365936879278374,"score_spread":0.364732499419929,"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."}}