{"id":"W3201338671","doi":"10.3390/robotics10030106","title":"Socially Assistive Robots Helping Older Adults through the Pandemic and Life after COVID-19","year":2021,"lang":"en","type":"article","venue":"Robotics","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"Baycrest Hospital; Canadian Institute for Advanced Research; Toronto Rehabilitation Institute; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Pandemic; Loneliness; Workload; Isolation (microbiology); Coronavirus disease 2019 (COVID-19); Social isolation; Population; Robot; Psychology; Public relations; Business; Internet privacy; Medicine; Computer science; Political science; Environmental health; Social psychology; Artificial intelligence; Psychiatry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003763732,0.0001704955,0.0002362979,0.00003134878,0.0009244853,0.0001209997,0.0002939023,0.0003357819,0.0001030529],"category_scores_gemma":[0.002427933,0.0001448084,0.00007823441,0.0003941545,0.0007708787,0.0001900198,0.0002243774,0.0003730112,0.00003333332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002035038,"about_ca_system_score_gemma":0.001427264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006624365,"about_ca_topic_score_gemma":0.01508251,"domain_scores_codex":[0.9981622,0.0003229188,0.0002434461,0.0004182591,0.0003727067,0.000480486],"domain_scores_gemma":[0.9986753,0.0005240272,0.0001188636,0.000301104,0.0001712109,0.0002094737],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001863383,0.0004639979,0.4372653,0.0003073639,0.0005688043,0.0006691894,0.3678429,0.004358402,0.00005631742,0.1452811,0.0208219,0.02217842],"study_design_scores_gemma":[0.006181265,0.000141488,0.6098703,0.0008281948,0.0006420664,0.00009109337,0.2439186,0.0008489744,0.000145451,0.05282634,0.08213095,0.002375268],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3942112,0.01647124,0.1230026,0.4457827,0.003310136,0.002581606,0.00008884025,0.002483725,0.01206804],"genre_scores_gemma":[0.9835259,0.0009784143,0.005435293,0.00879522,0.000314216,0.00003509099,0.000005415843,0.00002383516,0.0008866703],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5893146,"threshold_uncertainty_score":0.8416395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03005822261370221,"score_gpt":0.3159513015630428,"score_spread":0.2858930789493406,"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."}}