{"id":"W2152199276","doi":"10.4230/dagsemproc.05382.3","title":"Attention Demands in Text Entry Interfaces","year":2006,"lang":"en","type":"article","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Computer science; Argument (complex analysis); Perception; Text entry; Cognition; Interface (matter); Human–computer interaction; Cognitive load; Word (group theory); Natural language processing; Cognitive psychology; Linguistics; Psychology","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":[0.002155686,0.000656406,0.0005987221,0.001054553,0.0008423043,0.004639698,0.001453423,0.00197791,0.01251397],"category_scores_gemma":[0.03558537,0.0008814423,0.0003341362,0.001171495,0.0008951097,0.004969469,0.001969491,0.001441023,0.001998372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001947468,"about_ca_system_score_gemma":0.0006797564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003918336,"about_ca_topic_score_gemma":0.001932865,"domain_scores_codex":[0.9972267,0.000745385,0.0002188245,0.0004742874,0.001036913,0.000297923],"domain_scores_gemma":[0.9822733,0.01303951,0.001019727,0.0008944487,0.001994928,0.0007781421],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.006494426,0.001347763,0.04989811,0.003629881,0.0002319676,0.002212806,0.01770168,0.03361201,0.1939904,0.2951467,0.02080123,0.3749331],"study_design_scores_gemma":[0.0006059906,0.001408715,0.2555507,0.0005111408,0.0003975361,0.002159413,0.006351149,0.1717308,0.04074752,0.4858856,0.03422868,0.000422795],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7224398,0.005619829,0.1242818,0.00718245,0.0004852735,0.0003862485,0.001069806,0.00109469,0.1374401],"genre_scores_gemma":[0.9829599,0.0008951004,0.005062633,0.0003466531,0.0002130716,0.0001971034,0.0003201639,0.0001577569,0.009847626],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01251397,"threshold_uncertainty_score":0.04186338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006460817766876849,"score_gpt":0.2366786180387627,"score_spread":0.2302178002718858,"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."}}