{"id":"W4301039200","doi":"10.17615/ad08-kd63","title":"Graph-guided joint prediction of class label and clinical scores for the Alzheimer’s disease","year":2020,"lang":"en","type":"article","venue":"UNC Libraries","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institutes of Health; Genentech; IXICO; Servier; Eisai; BioClinica; Amorfix Life Sciences; National Cancer Institute; Medpace; Biogen; Elan; Novartis; AstraZeneca; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; Pfizer; Synarc; Alzheimer's Association; National Science Foundation","keywords":"Class (philosophy); Graph; Disease; Joint (building); Joint disease; Artificial intelligence; Computer science; Medicine; Psychology; Mathematics; Combinatorics; Internal medicine; Pathology; Engineering; Alternative medicine","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":[0.0001088672,0.00007960806,0.00010946,0.000008175277,0.0000720922,0.00003491287,0.0001002362,0.00007583385,0.000004200479],"category_scores_gemma":[0.0000939767,0.00005394271,0.00007835529,0.00003531144,0.0002292004,0.000008269892,0.0001139135,0.00005391007,5.314238e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":5.5809e-7,"about_ca_system_score_gemma":0.00006293758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001881147,"about_ca_topic_score_gemma":0.000001445192,"domain_scores_codex":[0.9994226,0.00001865516,0.0002753007,0.0001331963,0.00005198914,0.00009830895],"domain_scores_gemma":[0.9995759,0.00004470464,0.00009244884,0.0001578906,0.00003153506,0.00009755442],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002879004,0.0002805671,0.07421795,0.0004586597,0.002247953,0.000002366916,0.00102521,0.0005208013,0.01030837,0.2477585,0.6007109,0.05958977],"study_design_scores_gemma":[0.01098092,0.004735055,0.1266172,0.000150168,0.002123874,0.00001006748,0.001085279,0.2018568,0.05209644,0.1591962,0.4399492,0.001198801],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6260486,0.07995381,0.2342932,0.04813032,0.002355331,0.004333188,0.002367833,0.0001623334,0.002355294],"genre_scores_gemma":[0.9890951,0.0005266622,0.006480837,0.00290466,0.0006651021,0.00002506125,0.0002238839,0.00001788034,0.00006082575],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3630464,"threshold_uncertainty_score":0.219972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07063285646014912,"score_gpt":0.2752080064789691,"score_spread":0.20457515001882,"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."}}