{"id":"W3176794761","doi":"10.1145/3461778.3462031","title":"Machine Body Language: Expressing a Smart Speaker’s Activity with Intelligible Physical Motion","year":2021,"lang":"en","type":"article","venue":"","topic":"Social Robot Interaction and HRI","field":"Psychology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Autodesk (Canada)","funders":"European Research Council; European Commission; Aarhus Universitet","keywords":"Computer science; Motion (physics); Speech recognition; Body language; Artificial intelligence; Natural language processing; Linguistics; Philosophy","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":[0.0009413536,0.0005632006,0.0001686778,0.0003174616,0.0005274814,0.001383553,0.0005617702,0.000889776,0.005051359],"category_scores_gemma":[0.003594273,0.0001814378,0.0002560831,0.0001465664,0.001943624,0.001753654,0.002402761,0.0005370283,0.001048723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002629489,"about_ca_system_score_gemma":0.000279521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005160383,"about_ca_topic_score_gemma":0.0007954771,"domain_scores_codex":[0.9993993,0.0003296399,0.0000243824,0.00007628128,0.0001077837,0.00006253227],"domain_scores_gemma":[0.9990786,0.0005095334,0.00009369545,0.00009747758,0.00009590421,0.0001247451],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001218467,0.0002354081,0.01249573,0.002802474,0.00009076225,0.002577992,0.1644893,0.003717072,0.4887444,0.0563901,0.01469773,0.2525405],"study_design_scores_gemma":[0.000316811,0.003903624,0.06131253,0.001730601,0.0003843467,0.0111271,0.1003159,0.04433938,0.1405489,0.05048826,0.5847692,0.0007633922],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5665469,0.001778516,0.3427601,0.003770353,0.0006350695,0.0004769435,0.0005639382,0.003226347,0.08024193],"genre_scores_gemma":[0.8972057,0.000460603,0.08807722,0.0007906369,0.0001127651,0.0003930602,0.0002273135,0.0002137291,0.01251901],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005051359,"threshold_uncertainty_score":0.01689845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02985483490066669,"score_gpt":0.3759826447780515,"score_spread":0.3461278098773848,"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."}}