{"id":"W4367849368","doi":"10.32920/22734329.v1","title":"Towards Alzheimer's Disease Classification through Transfer Learning","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Transfer of learning; Artificial intelligence; Deep learning; Computer science; Neuroimaging; Benchmark (surveying); Machine learning; Deep neural networks; Training set; Artificial neural network; Entropy (arrow of time); Pattern recognition (psychology); Psychology; Neuroscience; Cartography","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":[0.001737769,0.00130642,0.0009892192,0.002032651,0.0003685301,0.001073755,0.001547102,0.001611904,0.002461822],"category_scores_gemma":[0.003535337,0.0003311444,0.0009297326,0.00118473,0.0006961766,0.001349537,0.001548549,0.001614379,0.002156959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007194119,"about_ca_system_score_gemma":0.0009175871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004378577,"about_ca_topic_score_gemma":0.003180929,"domain_scores_codex":[0.9994555,0.000148755,0.00003194515,0.0001642592,0.0001184906,0.00008101775],"domain_scores_gemma":[0.998993,0.0003905964,0.00009036103,0.000193965,0.0002503944,0.00008161695],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003595286,0.0003978448,0.00801947,0.0001437547,0.0002082694,0.0002435029,0.00009614699,0.1225593,0.01026161,0.003415448,0.01956132,0.8347337],"study_design_scores_gemma":[0.000022125,0.00007178777,0.001396652,0.00001921423,0.00002312482,0.0001159618,0.000028079,0.9802116,0.005225168,0.01138725,0.001485838,0.00001317881],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1975251,0.004834314,0.7746815,0.002569783,0.000387272,0.0002465292,0.001515608,0.01071267,0.007527156],"genre_scores_gemma":[0.8390564,0.001088393,0.144561,0.0008631524,0.0003603465,0.0001767873,0.003660702,0.0002035007,0.01002966],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004378577,"threshold_uncertainty_score":0.009190321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1945249201871302,"score_gpt":0.340440091460728,"score_spread":0.1459151712735977,"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."}}