{"id":"W2765441865","doi":"10.1016/j.jalz.2017.06.2611","title":"[TD‐P‐015]: LUDWIG: A CONVERSATIONAL ROBOT FOR PEOPLE WITH ALZHEIMER'S","year":2017,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Assistive Technology in Communication and Mobility","field":"Health Professions","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Rehabilitation Institute; University of Toronto; University Health Network","funders":"","keywords":"Session (web analytics); Partially observable Markov decision process; Robot; Computer science; Robotics; Conversation; Interview; Human–computer interaction; Hidden Markov model; Artificial intelligence; Software; Human–robot interaction; Confusion; Psychology; Markov model; Communication; Markov chain; World Wide Web; Machine learning; Sociology","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":[0.0005668584,0.0007772408,0.0002708366,0.0003348179,0.0007253737,0.0006909121,0.001020587,0.001354771,0.056903],"category_scores_gemma":[0.0011147,0.0001789498,0.0002480628,0.0003220596,0.0004120531,0.001168413,0.000804688,0.0006019558,0.02037812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005682005,"about_ca_system_score_gemma":0.0007399812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0095342,"about_ca_topic_score_gemma":0.01530173,"domain_scores_codex":[0.999795,0.00005409581,0.000011248,0.00006185989,0.00004777746,0.00003007413],"domain_scores_gemma":[0.999736,0.00003175147,0.000008789167,0.00002270171,0.0001006156,0.0001001215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006278091,0.0001686081,0.001014924,0.0003539593,0.00001797137,0.0008537149,0.001050543,0.001348423,0.01405114,0.00453759,0.7009507,0.2750246],"study_design_scores_gemma":[0.0001654821,0.0005106744,0.002463064,0.00007560176,0.00002613195,0.0007283893,0.0006680051,0.008840942,0.006883084,0.001645791,0.9779176,0.00007530975],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.08477463,0.0026061,0.2633763,0.01774171,0.01279659,0.003266019,0.01762122,0.0764025,0.5214149],"genre_scores_gemma":[0.1868112,0.001018244,0.08831522,0.004736855,0.0007153996,0.001538666,0.0200629,0.002522827,0.6942786],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.056903,"threshold_uncertainty_score":0.1903595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1153451576102742,"score_gpt":0.4181838504428483,"score_spread":0.302838692832574,"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."}}