{"id":"W2415809773","doi":"10.1145/2901790.2901815","title":"Tap-Kick-Click","year":2016,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Desk; Debugging; Computer science; Usability; Interface (matter); Foot (prosody); Input device; Code (set theory); User interface; Human–computer interaction; Computer graphics (images); Visualization; Simulation; Computer vision; Computer hardware; Artificial intelligence; Operating system; Programming language; Set (abstract data type)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00004146904,0.00005213405,0.00004704667,0.00003302601,0.00003293073,0.00002735276,0.0003845432,0.00001659416,0.0004857077],"category_scores_gemma":[0.00002241453,0.00002807767,0.00004015311,0.00006917673,0.00001616305,0.0005393791,0.0001095882,0.00002211171,0.003411681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001694094,"about_ca_system_score_gemma":0.00001333944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000104802,"about_ca_topic_score_gemma":0.000001939601,"domain_scores_codex":[0.9995335,0.00001389145,0.00006265438,0.0001636066,0.00007949195,0.0001468227],"domain_scores_gemma":[0.999576,0.00005683279,0.00001920366,0.0002518357,0.00005646469,0.00003967963],"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":[0.000003196501,0.00003825404,0.001343635,9.278632e-7,0.00001224646,0.00001229622,0.0001169453,5.291863e-8,0.322294,0.6075807,0.04694545,0.0216523],"study_design_scores_gemma":[0.0006324768,0.0001627472,0.05339541,0.0000247319,0.000004006491,0.0000353052,0.0000598859,0.0003397762,0.7055027,0.006371907,0.2331253,0.0003457587],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009644291,0.000007658489,0.771985,0.002874043,0.0003407549,0.00004373672,6.881613e-7,0.0000268996,0.215077],"genre_scores_gemma":[0.9773937,0.000004678344,0.00246828,0.001842514,0.00004376419,0.000006558686,1.545812e-7,0.000002764772,0.01823762],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9677494,"threshold_uncertainty_score":0.9973643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007991749248548632,"score_gpt":0.2262071538392525,"score_spread":0.2182154045907039,"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."}}