{"id":"W2754982177","doi":"10.1145/3132026","title":"Passive Haptic Training to Improve Speed and Performance on a Keypad","year":2017,"lang":"en","type":"article","venue":"Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Science Foundation","keywords":"Keypad; Haptic technology; Computer science; Text entry; Typing; Braille; Task (project management); Control (management); Words per minute; Learning effect; Human–computer interaction; Speech recognition; Multimedia; Simulation; Artificial intelligence; Reading (process); Computer hardware; Engineering; Operating system","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":[0.0003385849,0.0004304051,0.0003609562,0.0002244194,0.0001282922,0.000247439,0.0004349998,0.0003072292,0.005173804],"category_scores_gemma":[0.001080226,0.0001158953,0.0002017099,0.00009393103,0.0003830686,0.0004096475,0.0003803339,0.0005007479,0.0007508035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009523984,"about_ca_system_score_gemma":0.0002046062,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002792519,"about_ca_topic_score_gemma":0.0003706658,"domain_scores_codex":[0.9998173,0.00002913949,0.00002007097,0.00004993184,0.00004455424,0.00003903912],"domain_scores_gemma":[0.999473,0.000198358,0.00008865384,0.00009910954,0.00006554953,0.00007528411],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001383827,0.004606941,0.002290262,0.000572229,0.00003477618,0.0001199633,0.0002367569,0.0002520788,0.8676342,0.0001751302,0.0005758207,0.1221181],"study_design_scores_gemma":[0.0006946916,0.1213043,0.1461868,0.0002217073,0.0001467768,0.001701841,0.0004950727,0.003926593,0.7124186,0.0008099738,0.01203189,0.00006172392],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9870684,0.0004039106,0.009853434,0.0002272383,0.00007999882,0.0001492581,0.0001016212,0.0002376346,0.001878469],"genre_scores_gemma":[0.9840971,0.000449809,0.01074161,0.0001696879,0.00004264955,0.0001483822,0.0001013302,0.00003990835,0.00420947],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005173804,"threshold_uncertainty_score":0.01730812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03602311428892726,"score_gpt":0.2902666954669915,"score_spread":0.2542435811780643,"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."}}