{"id":"W3179912798","doi":"10.1145/3451343","title":"Robo Ludens","year":2021,"lang":"en","type":"article","venue":"ACM Transactions on Human-Robot Interaction","topic":"Social Robot Interaction and HRI","field":"Psychology","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Human–computer interaction; Computer science; Entertainment; Robot; Embodied cognition; Variety (cybernetics); Perspective (graphical); Game mechanics; Multimedia; 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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001332913,0.0003125793,0.0003165203,0.0003096602,0.0006582737,0.0001614278,0.0003168137,0.0002738544,0.06391802],"category_scores_gemma":[0.00007730064,0.0003552296,0.0004141791,0.0004276456,0.0000698928,0.0004025965,0.00001173149,0.0009626928,0.006784594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002969733,"about_ca_system_score_gemma":0.00004981912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003558767,"about_ca_topic_score_gemma":0.0006904518,"domain_scores_codex":[0.9977723,0.0002670164,0.0005356101,0.0006754498,0.0003132363,0.0004364298],"domain_scores_gemma":[0.997943,0.0003888088,0.0001786666,0.001051595,0.0002728878,0.0001650075],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002270929,0.01571477,0.001209189,0.0001331025,0.004561211,0.001210549,0.03351419,0.01762318,0.1729754,0.05124575,0.1156932,0.5838485],"study_design_scores_gemma":[0.008075984,0.001894417,0.04030016,0.0005956351,0.00101789,0.002422568,0.04920735,0.0003190395,0.1089947,0.01118077,0.7725794,0.00341211],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1801874,0.0003290045,0.3494103,0.01392846,0.04816798,0.00105281,0.00008985398,0.002092387,0.4047418],"genre_scores_gemma":[0.9272708,0.0000311578,0.0008697977,0.001799564,0.0004915217,0.0001536685,0.00006725228,0.00007075941,0.06924544],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7470834,"threshold_uncertainty_score":0.99989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1800345764994589,"score_gpt":0.4647037657234601,"score_spread":0.2846691892240012,"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."}}