{"id":"W1605729173","doi":"10.1007/978-3-642-12433-4_56","title":"Cluster Analysis and Decision Trees of MR Imaging in Patients Suffering Alzheimer’s","year":2010,"lang":"en","type":"book-chapter","venue":"Advances in intelligent and soft computing","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; Western University; Lawson Health Research Institute","funders":"","keywords":"Demographics; Decision tree; Cluster analysis; Disease; Cognitive impairment; Cluster (spacecraft); Cognition; Incidence (geometry); Computer science; Decision tree learning; Artificial intelligence; Psychology; Data mining; Medicine; Machine learning; Internal medicine; Mathematics; Psychiatry; Demography","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":[0.0003945665,0.0002382828,0.0005936131,0.0009216959,0.00004699452,0.00002605386,0.00008264687,0.0001077408,0.00005618679],"category_scores_gemma":[0.00008784342,0.0002139149,0.0001064948,0.0001333508,0.0001642403,0.0001175148,0.0002496653,0.0004560568,0.000001822572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002927322,"about_ca_system_score_gemma":0.00001899536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002941655,"about_ca_topic_score_gemma":0.0003218025,"domain_scores_codex":[0.9983624,0.00001718574,0.000591172,0.000421169,0.000352863,0.0002552232],"domain_scores_gemma":[0.9990141,0.0004258444,0.0001805732,0.0001523731,0.0001444221,0.0000826315],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001060449,0.00003624149,0.5407997,0.00004733613,0.00008627419,0.00000969629,0.0001599178,0.0000228562,0.00001153701,0.00008487716,7.415324e-7,0.4586348],"study_design_scores_gemma":[0.003409922,0.0005193352,0.9556174,0.003971894,0.001406692,0.00001149638,0.0002975389,0.01827577,0.00139467,0.009326083,0.004983456,0.0007857057],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9519988,0.01290642,0.0164948,0.00003539427,0.0001928335,0.0006560714,0.000005517302,0.00001824322,0.0176919],"genre_scores_gemma":[0.99455,0.002452602,0.002354974,0.00005009971,0.0000442295,0.000002512804,0.00003360163,0.0000231309,0.0004887843],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4578491,"threshold_uncertainty_score":0.8723196,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01402041255276374,"score_gpt":0.316400565865694,"score_spread":0.3023801533129303,"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."}}