{"id":"W3201504479","doi":"10.3389/frai.2021.678678","title":"Data-Driven Prediction of Fatigue in Parkinson’s Disease Patients","year":2021,"lang":"en","type":"article","venue":"Frontiers in Artificial Intelligence","topic":"Parkinson's Disease Mechanisms and Treatments","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Random forest; Rating scale; Motor symptoms; Parkinson's disease; Feature (linguistics); Physical medicine and rehabilitation; Psychology; Disease; Physical therapy; Medicine; Artificial intelligence; Computer science; Developmental psychology; Internal medicine","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":[0.001895102,0.0005042775,0.000635643,0.001442198,0.0001930417,0.0005409796,0.0003851279,0.000623222,0.0008321298],"category_scores_gemma":[0.007454255,0.0001681627,0.0007358175,0.0006613028,0.0001469861,0.0003134559,0.0002988122,0.0005798919,0.0002692164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005545576,"about_ca_system_score_gemma":0.0004237165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004883183,"about_ca_topic_score_gemma":0.003608107,"domain_scores_codex":[0.9994298,0.0002215907,0.00007250612,0.0001284717,0.00008662797,0.00006092703],"domain_scores_gemma":[0.9947702,0.003682296,0.0005121883,0.0001698754,0.0006497472,0.0002157222],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001018242,0.0004052233,0.8320104,0.0001278902,0.0003996015,0.0001813178,0.00009473661,0.09632969,0.0009235852,0.0001278973,0.001957956,0.06642339],"study_design_scores_gemma":[0.00005399115,0.0005413294,0.2816342,0.00004852982,0.00008466835,0.0003079054,0.00007959052,0.7147335,0.001040177,0.0007830635,0.0006618564,0.00003119367],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9866998,0.0004811127,0.00954995,0.0003155714,0.00003544467,0.00006622063,0.002377003,0.0001303614,0.0003446289],"genre_scores_gemma":[0.9936314,0.00006452752,0.003354501,0.00003282616,0.00001955887,0.00003642156,0.002747361,0.000004051605,0.000109342],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004883183,"threshold_uncertainty_score":0.01002234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07447003254239994,"score_gpt":0.3103519179825632,"score_spread":0.2358818854401633,"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."}}