{"id":"W4399873374","doi":"10.1148/ryai.240263","title":"Navigating Clinical Variability: Transfer Learning’s Impact on Imaging Model Performance","year":2024,"lang":"en","type":"letter","venue":"Radiology Artificial Intelligence","topic":"AI in cancer detection","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre Intégré de Santé et de Services Sociaux des Laurentides","funders":"","keywords":"Transfer of learning; Computer science; Artificial intelligence","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":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003073555,0.0006921061,0.0008544541,0.0001672656,0.0003576593,0.0002918626,0.001831014,0.001233315,0.00008452224],"category_scores_gemma":[0.0003387562,0.0006088761,0.0006046962,0.0006015697,0.0005673044,0.0004307577,0.0002466203,0.01191778,0.001171684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005895923,"about_ca_system_score_gemma":0.0004711594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003470621,"about_ca_topic_score_gemma":0.000002054022,"domain_scores_codex":[0.9939683,0.001052531,0.001450217,0.002014533,0.0004984426,0.001015953],"domain_scores_gemma":[0.9966175,0.001638116,0.0002104514,0.001233546,0.0001728742,0.0001275185],"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":[0.00007904953,0.00005871218,0.0004771035,0.0001709125,0.0001637039,0.0003062125,0.001014009,0.2162859,0.00007826825,0.002936902,0.07998127,0.6984479],"study_design_scores_gemma":[0.00001927343,0.0004802345,0.00002817172,0.0002600209,0.00004890758,0.0002020436,0.000009017208,0.9639894,0.0009903784,0.02246422,0.01090282,0.0006055445],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01147947,0.0001784945,0.8396998,0.141553,0.005326115,0.0003936822,0.00001378964,0.0007399562,0.0006156614],"genre_scores_gemma":[0.8190873,0.0003292068,0.006259672,0.1652155,0.008340332,0.0001483636,0.00004272186,0.0001564374,0.0004204479],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8334401,"threshold_uncertainty_score":0.9996362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06518302432630502,"score_gpt":0.3727762012536321,"score_spread":0.3075931769273271,"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."}}