{"id":"W4408324923","doi":"10.1109/globecom52923.2024.10901405","title":"Optimized-Constrained Transfer Learning: Application for Stroke Prediction","year":2024,"lang":"en","type":"article","venue":"","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Computer science; Transfer of learning; Artificial intelligence; Machine learning","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":[0.0001750228,0.00008371395,0.00006723004,0.00009476561,0.0001452258,0.00009629827,0.00007317398,0.00006060065,0.0001776682],"category_scores_gemma":[0.0001168618,0.00007531462,0.00008208513,0.0002054881,0.00004141461,0.000178138,0.000004024749,0.000138167,0.0001016212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003654344,"about_ca_system_score_gemma":0.00003477632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001797345,"about_ca_topic_score_gemma":8.220685e-7,"domain_scores_codex":[0.9991493,0.00004362277,0.0001707067,0.0003727936,0.0001301701,0.0001333997],"domain_scores_gemma":[0.9996037,0.0002036826,0.00001251178,0.0001077209,0.00002374022,0.00004864204],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003985015,0.0000248608,0.000005263329,0.00002813007,0.000003540626,3.96161e-7,0.00009134791,0.0007143471,0.8640317,0.07903478,0.0003110124,0.0557148],"study_design_scores_gemma":[0.0003614712,0.00009296608,0.00006911725,0.000006369213,0.00001470759,0.00001933643,0.00009920148,0.4538184,0.4489504,0.000510449,0.09596872,0.00008884722],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0128782,0.00001480843,0.9647508,0.001732944,0.0004068859,0.0006601519,0.00003749339,0.001115909,0.01840281],"genre_scores_gemma":[0.9865795,0.00001873351,0.0005860674,0.000196856,0.0001221444,0.0003969049,0.00001508027,0.00001874003,0.01206592],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9737014,"threshold_uncertainty_score":0.3071241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02908610096800107,"score_gpt":0.2676154371467095,"score_spread":0.2385293361787085,"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."}}