{"id":"W4396779895","doi":"10.1126/science.adp0670","title":"Imaging without barriers","year":2024,"lang":"en","type":"letter","venue":"Science","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada); Montreal Neurological Institute and Hospital","funders":"","keywords":"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":[0.001170098,0.0004080571,0.0003325554,0.0002162428,0.0009864898,0.001859828,0.0007442527,0.007890312,0.00609158],"category_scores_gemma":[0.004857579,0.0002603867,0.0003022006,0.00009278477,0.003052662,0.002489167,0.001118122,0.006864873,0.005774577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00139088,"about_ca_system_score_gemma":0.0006022445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005285781,"about_ca_topic_score_gemma":0.000960297,"domain_scores_codex":[0.9990638,0.0002339879,0.0000272651,0.0001149485,0.0004528086,0.0001072571],"domain_scores_gemma":[0.9984498,0.0009700294,0.00007860371,0.0001534534,0.0001938722,0.0001542704],"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":[0.0001695041,0.00005696688,0.0003434173,0.0003183856,0.00002603951,0.003294176,0.0001847601,0.0003303182,0.03388303,0.1665301,0.7238305,0.0710328],"study_design_scores_gemma":[0.00003979338,0.0000664785,0.00009817954,0.0001090537,0.000008028635,0.002692723,0.00008645255,0.0008172006,0.008355625,0.04223217,0.9454748,0.0000194672],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.005201377,0.03377452,0.0218767,0.7777781,0.03215662,0.00006966134,0.00008832377,0.0005764431,0.1284784],"genre_scores_gemma":[0.2405275,0.02924838,0.01653467,0.5605159,0.0277345,0.0003226564,0.0001457539,0.0002122439,0.1247586],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.007890312,"threshold_uncertainty_score":0.02037841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01410877645956331,"score_gpt":0.3490223750081511,"score_spread":0.3349135985485878,"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."}}