{"id":"W4205185790","doi":"10.24251/hicss.2022.257","title":"Assisting People of Determination and the Elderly Using Social Robot: A Case Study","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Robot; Computer science; Human–computer interaction; Artificial intelligence","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","sts"],"consensus_categories":[],"category_scores_codex":[0.003974172,0.0004318421,0.0006559839,0.0006483851,0.001808197,0.0004347504,0.003496018,0.000104934,0.00004406056],"category_scores_gemma":[0.00008009242,0.0002844122,0.0002763,0.001757935,0.001540655,0.001205752,0.0005766149,0.0005131556,0.000001545315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000365876,"about_ca_system_score_gemma":0.0002878914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007628029,"about_ca_topic_score_gemma":0.00008002322,"domain_scores_codex":[0.9941801,0.0000724602,0.001535066,0.0007358816,0.003059377,0.0004170441],"domain_scores_gemma":[0.9940287,0.0002092153,0.001737481,0.0001653189,0.003779233,0.00008007224],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001126732,0.0001557804,0.007857683,0.0002015873,0.0001095001,0.000001832913,0.01166139,0.001615701,0.00107105,0.9765203,0.0001025576,0.0005899353],"study_design_scores_gemma":[0.001097314,0.000524538,0.004730191,0.0006438807,0.00008935037,0.000414792,0.9780525,0.01315995,0.0003412384,0.000579161,0.00003740188,0.0003296722],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6947294,0.00001312234,0.00005963718,0.001351638,0.00155992,0.0010204,0.0004387252,0.00009048654,0.3007367],"genre_scores_gemma":[0.9992377,0.000004518059,0.0002216164,0.00002987865,0.0001305647,0.0001737643,0.000002559623,0.00002296013,0.0001764932],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9759411,"threshold_uncertainty_score":0.9999608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05330518037555829,"score_gpt":0.3046237810790581,"score_spread":0.2513186007034998,"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."}}