{"id":"W2505462564","doi":"10.1007/978-3-319-41267-2_72","title":"Comparison of Two Methods to Control the Mouse Using a Keypad","year":2016,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Keypad; Computer science; Software; Human–computer interaction; Throughput; Pointing device; Control (management); Component (thermodynamics); Input device; Computer hardware; Artificial intelligence; Operating system; Wireless","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":[0.001344212,0.001433015,0.0009390197,0.001768005,0.0003292588,0.001072245,0.001885308,0.001291772,0.01013282],"category_scores_gemma":[0.006333974,0.0004576892,0.0005510308,0.0006891743,0.0003470305,0.001406889,0.0008777969,0.0004955643,0.001632003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003597807,"about_ca_system_score_gemma":0.0005254563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002463893,"about_ca_topic_score_gemma":0.002013084,"domain_scores_codex":[0.9985158,0.0003876383,0.0001455769,0.0002632902,0.0005762232,0.0001114711],"domain_scores_gemma":[0.994194,0.003849038,0.0002109777,0.0004277518,0.001137325,0.0001809685],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.01667925,0.001712616,0.002403539,0.002807693,0.0006056718,0.0001310518,0.0004312221,0.002006185,0.1483005,0.001074383,0.003399237,0.8204488],"study_design_scores_gemma":[0.01282157,0.05489002,0.1329159,0.001173783,0.006843934,0.004845503,0.001414989,0.2442346,0.4795706,0.003541011,0.05681405,0.0009339483],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4087793,0.02070477,0.5455014,0.0003785746,0.001628785,0.00152785,0.0008753337,0.008235744,0.01236823],"genre_scores_gemma":[0.7046989,0.005446737,0.2648405,0.0004565843,0.0002735321,0.001482578,0.001114812,0.000969614,0.02071669],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01013282,"threshold_uncertainty_score":0.03389764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04873087243238862,"score_gpt":0.370258369383117,"score_spread":0.3215274969507284,"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."}}