{"id":"W2748736579","doi":"10.11575/prism/27473","title":"Proxemic Interactions in Ubiquitous Computing Ecologies","year":2011,"lang":"en","type":"dissertation","venue":"UCL Discovery (University College London)","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Proxemics; Ubiquitous computing; Human–computer interaction; Leverage (statistics); Computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009262458,0.0003639029,0.0002138702,0.0009686624,0.001594877,0.005273317,0.0004731854,0.0008305269,0.007144107],"category_scores_gemma":[0.003165792,0.0003027716,0.0002424265,0.0009110039,0.002710363,0.004873343,0.004479893,0.000953858,0.0005065654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009294669,"about_ca_system_score_gemma":0.0006448789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001653712,"about_ca_topic_score_gemma":0.002080671,"domain_scores_codex":[0.9988319,0.0006263003,0.00005066643,0.0001404827,0.0002317815,0.000118759],"domain_scores_gemma":[0.9992256,0.0003921169,0.00007506418,0.00008081624,0.0001059434,0.0001205365],"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":[0.0001079981,0.00007233951,0.00286039,0.0004606297,0.00002699284,0.0005593223,0.03134954,0.009151032,0.005181852,0.7971126,0.00591845,0.1471989],"study_design_scores_gemma":[0.00005853902,0.0002173504,0.01416723,0.0005695625,0.00006111414,0.001024458,0.02807294,0.03503266,0.004279387,0.472692,0.4437077,0.0001169991],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.2269609,0.007915298,0.4969333,0.006539625,0.0003072267,0.0002009639,0.0002018479,0.0008131692,0.2601277],"genre_scores_gemma":[0.9321096,0.002318308,0.04097936,0.000399566,0.0001010808,0.0001556747,0.0001013135,0.00008766819,0.02374742],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.007144107,"threshold_uncertainty_score":0.02389938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01836256685312574,"score_gpt":0.2478833581938669,"score_spread":0.2295207913407412,"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."}}