{"id":"W2166171360","doi":"","title":"Improving bimanual human-computer interaction using force display","year":2006,"lang":"en","type":"dissertation","venue":"Summit (Simon Fraser University)","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Haptic technology; Task (project management); Human–computer interaction; Computer science; Fitts's law; Simulation; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003218437,0.0003508467,0.0001716082,0.0002688871,0.0001353316,0.0003509341,0.0002525891,0.0002633428,0.006228419],"category_scores_gemma":[0.001374096,0.00007871513,0.0001041241,0.0001524844,0.0001335519,0.0005093386,0.000534227,0.0001468186,0.0005291901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009786134,"about_ca_system_score_gemma":0.0001356578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004260834,"about_ca_topic_score_gemma":0.0006444723,"domain_scores_codex":[0.9997873,0.00006292374,0.00001131371,0.0000374552,0.00007670928,0.00002431258],"domain_scores_gemma":[0.9997597,0.0001467886,0.00002293245,0.0000151924,0.0000370566,0.00001831638],"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":[0.0009899912,0.001184767,0.002585617,0.0003585957,0.00002960133,0.000177888,0.0006096324,0.002226518,0.5259926,0.0009058453,0.001273539,0.4636653],"study_design_scores_gemma":[0.000996939,0.01334655,0.2042283,0.0001728052,0.0002181548,0.00333718,0.001150405,0.08879758,0.6364843,0.006795558,0.04432533,0.0001468981],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9071075,0.001794223,0.08203375,0.0002357763,0.00003250703,0.0001253473,0.00006113365,0.000395775,0.008214009],"genre_scores_gemma":[0.9473914,0.000714271,0.0471562,0.00006201907,0.00002013643,0.00005704421,0.00005941335,0.0000221065,0.004517512],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006228419,"threshold_uncertainty_score":0.02083611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02492679394969414,"score_gpt":0.2692742419065574,"score_spread":0.2443474479568633,"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."}}