{"id":"W2950062006","doi":"10.1109/access.2019.2920448","title":"Transfer Learning With Intelligent Training Data Selection for Prediction of Alzheimer’s Disease","year":2019,"lang":"en","type":"article","venue":"IEEE Access","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":180,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Ryerson University","keywords":"Computer science; Transfer of learning; Selection (genetic algorithm); Artificial intelligence; Machine learning; Training (meteorology); Disease; Medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00187651,0.001393739,0.001004282,0.0008927504,0.0003195078,0.0006142483,0.001692983,0.00129943,0.001434988],"category_scores_gemma":[0.003934269,0.0003610589,0.0007451064,0.0007739341,0.0005290008,0.001169183,0.0009372463,0.001805765,0.0006319053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008754089,"about_ca_system_score_gemma":0.0009025998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006609648,"about_ca_topic_score_gemma":0.004589478,"domain_scores_codex":[0.9995932,0.0001351659,0.0000217375,0.0001184129,0.00006636289,0.00006511713],"domain_scores_gemma":[0.9990963,0.0005014989,0.0000645204,0.0001077459,0.000175965,0.0000539971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000559004,0.0005122965,0.005848412,0.00009014505,0.0001445188,0.0002104169,0.00008852054,0.6601315,0.006654092,0.001702129,0.008467808,0.3155911],"study_design_scores_gemma":[0.000008995844,0.00002972953,0.0003066484,0.00000480199,0.000008109864,0.00001221183,0.000005349874,0.9972419,0.001062069,0.001155374,0.0001602778,0.000004435726],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3614157,0.005857216,0.6166462,0.001909128,0.0003481138,0.0002215349,0.0008066698,0.008281832,0.00451347],"genre_scores_gemma":[0.9524357,0.0004382244,0.04331742,0.0003618257,0.00009844156,0.000115511,0.0009061276,0.0001032576,0.002223573],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006609648,"threshold_uncertainty_score":0.01314235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2197828532823449,"score_gpt":0.3483505821977063,"score_spread":0.1285677289153614,"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."}}