{"id":"W4405961022","doi":"10.1093/geroni/igae098.1113","title":"END-USER PERSPECTIVES ON POLICIES FOR SOCIAL ROBOTICS WITH AGING APPLICATIONS","year":2024,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Robotics; Artificial intelligence; Computer science; Human–computer interaction; Robot","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":[0.06433105,0.0005743806,0.0003725793,0.001384702,0.008150973,0.01309157,0.001477706,0.006440234,0.004485101],"category_scores_gemma":[0.08269954,0.0003926788,0.0006668663,0.0008757623,0.01144674,0.01016561,0.008558541,0.004767659,0.0006918606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008876279,"about_ca_system_score_gemma":0.007303797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004019904,"about_ca_topic_score_gemma":0.003234627,"domain_scores_codex":[0.9403386,0.04907797,0.001949953,0.0014041,0.003866608,0.003362893],"domain_scores_gemma":[0.8938808,0.08583876,0.005568109,0.003175225,0.008079591,0.003457508],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002017329,0.0003276065,0.01871283,0.0005766925,0.00002387102,0.001157167,0.8029251,0.001093527,0.002881513,0.1257277,0.005879032,0.0404932],"study_design_scores_gemma":[0.00003750592,0.000331732,0.006696759,0.001612817,0.00003744081,0.0004761209,0.7716721,0.002369502,0.002873645,0.02009867,0.1936732,0.000120548],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8038723,0.001118982,0.02602573,0.05235345,0.0003639823,0.0004783287,0.0001478096,0.0001628876,0.1154766],"genre_scores_gemma":[0.988758,0.0003233197,0.004069513,0.004096915,0.00004448069,0.0002136689,0.00002559925,0.00002987475,0.002438665],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06433105,"threshold_uncertainty_score":0.3402191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02029753837889222,"score_gpt":0.2955455717468233,"score_spread":0.2752480333679311,"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."}}