{"id":"W4404553415","doi":"10.1145/3687272.3688310","title":"Research by Design: Mirrly a Humanoid Robot for Child-Robot Interaction","year":2024,"lang":"en","type":"article","venue":"","topic":"Social Robot Interaction and HRI","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Humanoid robot; Robot; Computer science; Human–computer interaction; Simulation; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005390731,0.001065459,0.0004565839,0.0007027598,0.001182738,0.002260885,0.001378647,0.001187131,0.01118443],"category_scores_gemma":[0.006376183,0.0004297427,0.0006021329,0.0002921325,0.003106563,0.002312726,0.002779361,0.001651617,0.002908878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009300116,"about_ca_system_score_gemma":0.002594316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006860508,"about_ca_topic_score_gemma":0.001609232,"domain_scores_codex":[0.9968502,0.001934374,0.0001008841,0.0003687728,0.0005756884,0.0001700914],"domain_scores_gemma":[0.9977131,0.0009084357,0.0001671565,0.0003441714,0.0004454006,0.0004218195],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008345461,0.001259441,0.007401881,0.004335026,0.0001040524,0.001134649,0.02075883,0.004948647,0.09859816,0.1641224,0.04845549,0.648047],"study_design_scores_gemma":[0.0008349884,0.009109858,0.006995467,0.001456675,0.0002139931,0.003073173,0.008489002,0.01654782,0.04884477,0.03516443,0.8689975,0.000272385],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09411781,0.00226601,0.7862436,0.005636967,0.001108153,0.004997587,0.0003819697,0.00410784,0.1011401],"genre_scores_gemma":[0.2478917,0.001437937,0.7082933,0.001739357,0.0001288185,0.005419895,0.000291749,0.0005883147,0.03420897],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01118443,"threshold_uncertainty_score":0.03741562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2676184162104801,"score_gpt":0.5417453812743923,"score_spread":0.2741269650639122,"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."}}