{"id":"W2032424390","doi":"10.1145/2702123.2702185","title":"Grip Change as an Information Side Channel for Mobile Touch Interaction","year":2015,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Mobile device; Tilt sensor; Channel (broadcasting); Point (geometry); Smartwatch; Tilt (camera); Mobile interaction; Motion (physics); Human–computer interaction; Computer vision; Simulation; Real-time computing; Engineering; Embedded system; Telecommunications; Wearable computer","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001254838,0.00009161422,0.00008112616,0.000117993,0.00006180532,0.0001524274,0.0002878838,0.0000411676,0.00002035679],"category_scores_gemma":[0.00004966856,0.00007972095,0.000045439,0.0001140467,0.000007779003,0.008558847,0.00007578744,0.00006007866,0.0004766495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007370851,"about_ca_system_score_gemma":0.00003427701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002842776,"about_ca_topic_score_gemma":0.00002320322,"domain_scores_codex":[0.9993751,0.00002122706,0.0001446089,0.0001458016,0.0001350973,0.0001781885],"domain_scores_gemma":[0.9991772,0.00003303654,0.00007995142,0.0002156991,0.0003910408,0.0001030719],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001016337,0.001115156,0.0002704668,0.0001450857,0.0001799044,0.00001267596,0.1621427,0.0006860648,0.01761797,0.3692749,0.1531276,0.2944111],"study_design_scores_gemma":[0.002375256,0.005060775,0.00171927,0.00005546312,0.00002039405,0.0000961298,0.02310476,0.4286189,0.2089034,0.01246171,0.3167172,0.0008667015],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06261974,0.00001289654,0.8891752,0.001123025,0.002572196,0.0009925152,0.000009193011,0.0000900868,0.04340517],"genre_scores_gemma":[0.9934258,0.000002629295,0.001901226,0.00359307,0.0002005067,0.0003303922,0.00006301287,0.000004760533,0.0004785469],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9308061,"threshold_uncertainty_score":0.6204957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06793888484387334,"score_gpt":0.3292745117421858,"score_spread":0.2613356268983125,"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."}}