{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006335279,0.0002921294,0.0006630086,0.0004251504,0.0005927312,0.001758934,0.0008825555,0.005372089,0.002938593],"category_scores_gemma":[0.06279204,0.0002568073,0.0005121771,0.0005207934,0.0009377786,0.00216374,0.0008808043,0.005891217,0.001650059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000865788,"about_ca_system_score_gemma":0.001046498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00301779,"about_ca_topic_score_gemma":0.003814838,"domain_scores_codex":[0.9986546,0.0007400044,0.00008558562,0.0001629535,0.0002704409,0.0000863666],"domain_scores_gemma":[0.9722171,0.02367432,0.0004978669,0.001578108,0.001477735,0.0005548357],"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":[0.001831495,0.0006279093,0.02787635,0.0001733079,0.0001640673,0.001853283,0.0005488879,0.08415864,0.007969713,0.01101648,0.1414516,0.7223282],"study_design_scores_gemma":[0.000344064,0.0007875905,0.01171241,0.0001120843,0.0001071857,0.005614222,0.0003949155,0.8090242,0.01526724,0.1079889,0.04850427,0.0001429704],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"methods","genre_scores_codex":[0.1947124,0.003094613,0.2143351,0.5561159,0.00450267,0.0001277254,0.0005741889,0.002070773,0.02446662],"genre_scores_gemma":[0.9004793,0.0009949146,0.04678431,0.04020304,0.00400599,0.0001203736,0.0002658474,0.0005183849,0.006627867],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.006335279,"threshold_uncertainty_score":0.03350455,"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."}}