{"id":"W1975016730","doi":"10.1145/1347390.1347431","title":"Making sense of group interaction in an ambient intelligent environment for physical play","year":2008,"lang":"en","type":"article","venue":"","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Human–computer interaction; Embodied cognition; Interaction model; Computer science; Interaction design; Heuristics; Group cohesiveness; Social relation; Cohesion (chemistry); Group (periodic table); Factor (programming language); Psychology; Artificial intelligence; Social psychology; World Wide Web","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":[],"consensus_categories":[],"category_scores_codex":[0.0001291763,0.0001069961,0.0001442596,0.00025097,0.00005539116,0.00001260682,0.0002172847,0.00005183462,0.00001675932],"category_scores_gemma":[0.00001435858,0.0001006549,0.00004733052,0.0001641716,0.00007086902,0.0005609212,0.0001214559,0.0001613256,0.00002142854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001819876,"about_ca_system_score_gemma":0.000008088708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001711288,"about_ca_topic_score_gemma":0.00004235871,"domain_scores_codex":[0.9990692,0.00003979569,0.0002721619,0.0003108761,0.0001392773,0.0001686533],"domain_scores_gemma":[0.9994319,0.00007078598,0.000127604,0.0003128257,0.0000413881,0.00001549031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003352001,0.003716369,0.003842446,0.00003861322,0.00006822926,0.00008430916,0.01799254,0.00301157,0.3906579,0.5034646,0.0005507176,0.0762375],"study_design_scores_gemma":[0.0007180572,0.00216527,0.01886672,0.00007281527,0.000006319951,0.0001698964,0.0007564817,0.2949743,0.6734243,0.005188658,0.003256206,0.0004009772],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5660653,0.000001384562,0.433398,0.0000668199,0.0001463022,0.0001555034,5.793207e-7,0.00004083645,0.0001253239],"genre_scores_gemma":[0.9777119,0.000002646393,0.0220517,0.0001042646,0.00003426547,0.00004008417,0.000004050971,0.000006732694,0.00004431621],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4982759,"threshold_uncertainty_score":0.4104588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07788270465131544,"score_gpt":0.3342330297316918,"score_spread":0.2563503250803764,"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."}}