{"id":"W4400729102","doi":"10.1109/jtehm.2024.3430035","title":"XAI-Based Assessment of the AMURA Model for Detecting Amyloid-β and Tau Microstructural Signatures in Alzheimer’s Disease","year":2024,"lang":"en","type":"article","venue":"IEEE Journal of Translational Engineering in Health and Medicine","topic":"Alzheimer's disease research and treatments","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministero dell'Istruzione e del Merito; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Fondazione Cassa di Risparmio di Verona Vicenza Belluno e Ancona; Eisai; Janssen Alzheimer Immunotherapy Research And Development; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; Ministero dell’Istruzione, dell’Università e della Ricerca; University of Southern California; Bristol-Myers Squibb; Eli Lilly and Company; Biogen; BioClinica; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association","keywords":"Disease; Alzheimer's disease; Amyloid (mycology); Amyloid β; Neuroscience; Computer science; Medicine; Pathology; Psychology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003975761,0.0001046618,0.0002693537,0.0002690457,0.00003068708,0.000005559953,0.00003580836,0.00003362186,0.000002735301],"category_scores_gemma":[0.00007158922,0.00006489993,0.00005923059,0.0001479685,0.00005408979,0.00006061782,0.00000285303,0.0002760568,9.628992e-9],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005124443,"about_ca_system_score_gemma":0.0008780938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000247549,"about_ca_topic_score_gemma":0.000008752189,"domain_scores_codex":[0.9989512,0.0000224313,0.0004475621,0.0001050674,0.0002961198,0.0001776361],"domain_scores_gemma":[0.9992018,0.0002915169,0.0000733608,0.00005212499,0.00006382028,0.0003173568],"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":[0.003131698,0.0002811097,0.1054091,0.008939762,0.001916638,0.0002088515,0.001839227,0.8519086,0.004219379,0.0008294401,0.0001887209,0.02112746],"study_design_scores_gemma":[0.003745914,0.0003705085,0.1369577,0.002609849,0.0001608504,0.00002704238,0.00002491127,0.8556992,0.00009616267,0.0002333146,0.00002256326,0.00005198786],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8625541,0.1209666,0.006387359,0.009111761,0.0002243224,0.0006989734,0.0000447575,0.000008184976,0.000003945985],"genre_scores_gemma":[0.9970268,0.0003575226,0.002327609,0.0001432169,0.0001154672,0.000009826969,0.000006192786,0.00001200316,0.000001336487],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1344728,"threshold_uncertainty_score":0.2646542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03881161633079072,"score_gpt":0.3672062110015012,"score_spread":0.3283945946707105,"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."}}