{"id":"W4313554955","doi":"10.1109/tmi.2023.3234450","title":"Proportionally Fair Hospital Collaborations in Federated Learning of Histopathology Images","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; University of Waterloo","funders":"Mayo Clinic","keywords":"Federated learning; Computer science; Artificial intelligence; Function (biology); Scheme (mathematics); Machine learning; Data sharing; Health care; Data modeling; Database; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006928144,0.0001297782,0.0001989198,0.0005538831,0.0001958001,0.00005680917,0.003784943,0.0001050254,0.00005506003],"category_scores_gemma":[0.004043432,0.0001323575,0.00004707444,0.001962761,0.0002853814,0.0005128505,0.0003254995,0.0006750377,0.00005337335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001042167,"about_ca_system_score_gemma":0.0003146949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004255834,"about_ca_topic_score_gemma":0.00002659907,"domain_scores_codex":[0.9981316,0.0001315277,0.0004152405,0.0004272502,0.0005708999,0.000323473],"domain_scores_gemma":[0.9983155,0.0002661545,0.0001048801,0.001091075,0.0001416586,0.00008070544],"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":[0.00005722086,0.002232656,0.01537862,0.0002332836,0.0000967616,0.003396583,0.001837459,0.01457201,0.03987531,0.003263882,0.1354015,0.7836547],"study_design_scores_gemma":[0.0008420384,0.0001333506,0.006413158,0.0001847757,0.000009996819,0.00005946496,0.0004459686,0.9616941,0.02013602,0.009055356,0.0006781468,0.0003476657],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02404578,0.00003134423,0.9204028,0.05357732,0.0006024624,0.0001544418,0.00001330028,0.0009913031,0.0001812516],"genre_scores_gemma":[0.9751673,0.00008269907,0.02443768,0.0001235599,0.00001337696,0.00006381095,0.00001049727,0.00001321194,0.00008780806],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9511216,"threshold_uncertainty_score":0.7033429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01508106752166137,"score_gpt":0.2775704834577507,"score_spread":0.2624894159360893,"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."}}