{"id":"W272750617","doi":"10.1007/978-3-319-17957-5_14","title":"PHEN: Parkinson Helper Emergency Notification System Using Bayesian Belief Network","year":2015,"lang":"en","type":"book-chapter","venue":"Lecture notes in business information processing","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Ontology; Context (archaeology); Bayesian network; Computer science; Parkinson's disease; Representation (politics); Disease; Artificial intelligence; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000976817,0.0007000558,0.000771163,0.0008009558,0.0003984429,0.0007719197,0.0009144649,0.0008107655,0.00004633746],"category_scores_gemma":[0.0002331764,0.0007137919,0.0001223334,0.001060158,0.00005920102,0.005622375,0.0002718781,0.0006433305,0.000160397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009276083,"about_ca_system_score_gemma":0.0007561258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005277968,"about_ca_topic_score_gemma":0.0000833438,"domain_scores_codex":[0.9960019,0.00008209831,0.001707857,0.0006191808,0.001037387,0.0005515787],"domain_scores_gemma":[0.9947683,0.00009977036,0.001975907,0.0008293478,0.002186786,0.0001399002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003905202,0.00002843498,0.0002122464,0.002828316,0.00005096954,0.00001172655,0.003037198,0.06314822,0.00002372317,0.007071142,0.0002831646,0.9232658],"study_design_scores_gemma":[0.0009854974,0.00003787735,0.0002419556,0.007885892,0.0001058906,0.0002661267,0.00007911845,0.8103983,0.0001144503,0.01372384,0.163828,0.002333037],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00003623454,0.001683471,0.9679828,0.0003612216,0.002363016,0.0007859198,0.00001663864,0.0005082788,0.02626243],"genre_scores_gemma":[0.9641036,0.0000794087,0.03231224,0.0003899224,0.001731773,0.0001066947,0.0004399449,0.0001310102,0.0007053417],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9640674,"threshold_uncertainty_score":0.9995313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03974464002549206,"score_gpt":0.2567701191237949,"score_spread":0.2170254790983028,"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."}}