{"id":"W2588515875","doi":"10.1145/2998181.2998247","title":"Flex-N-Feel","year":2017,"lang":"en","type":"article","venue":"","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":79,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"FLEX; Appropriation; Human–computer interaction; Computer science; Conversation; Multimedia; Psychology; Communication; Telecommunications","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":[0.0009427426,0.0008409286,0.0002781118,0.0003116386,0.0005431618,0.001123241,0.0008458151,0.0009191332,0.02502933],"category_scores_gemma":[0.003057789,0.000339444,0.000573166,0.0001563907,0.0006880416,0.001902812,0.00323519,0.0005786465,0.002509189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002097033,"about_ca_system_score_gemma":0.0003199071,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003459639,"about_ca_topic_score_gemma":0.0007424286,"domain_scores_codex":[0.9992938,0.0002291126,0.00004875526,0.0001235391,0.0002157857,0.00008910595],"domain_scores_gemma":[0.9991979,0.000264301,0.00007800647,0.000208227,0.0001082859,0.0001432802],"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":[0.001953011,0.0005514123,0.01448347,0.003889014,0.0001362226,0.002466335,0.01720197,0.003089967,0.2025269,0.02763821,0.0318216,0.694242],"study_design_scores_gemma":[0.0005865971,0.006112414,0.05517335,0.001687203,0.0004594414,0.01693327,0.01474152,0.01854943,0.09554643,0.02394878,0.7656249,0.0006365709],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.3701791,0.002424028,0.4557272,0.001454852,0.0007277659,0.001204606,0.00123064,0.006969091,0.1600827],"genre_scores_gemma":[0.8109065,0.0007638839,0.1366758,0.0009313878,0.00006282067,0.0009336542,0.0006101399,0.0005296424,0.04858619],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02502933,"threshold_uncertainty_score":0.08373147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03242533478573122,"score_gpt":0.3228546038662735,"score_spread":0.2904292690805422,"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."}}