{"id":"W1932882396","doi":"10.1109/icniconsmcl.2006.138","title":"M-learning: Overcoming the Usability Challenges of Mobile Devices","year":2006,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Usability; Mobile device; Computer science; Mobile technology; Mobile computing; Human–computer interaction; TRIPS architecture; Multimedia; Field (mathematics); Mobile Web; Mobile telephony; World Wide Web; Telecommunications; Mobile radio","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":[],"consensus_categories":[],"category_scores_codex":[0.0005192094,0.00006267807,0.0001107186,0.00002240925,0.00006734874,0.00003923612,0.0004983291,0.00003046087,0.00001460529],"category_scores_gemma":[0.00003293627,0.00003728405,0.00005035827,0.0001183857,0.00004271029,0.0001598438,0.0001158935,0.00005856662,0.0000247792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001108041,"about_ca_system_score_gemma":0.00002302007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007857505,"about_ca_topic_score_gemma":0.0003242825,"domain_scores_codex":[0.9992316,0.00009817033,0.0001828811,0.0001776537,0.0001714811,0.0001382446],"domain_scores_gemma":[0.9992314,0.0002510119,0.00007724528,0.0003741499,0.00004475842,0.00002146404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00001180755,0.0003206158,0.1008451,0.000172593,0.0000298633,0.000004828975,0.003268965,0.002116519,0.003980251,0.7763432,0.001625957,0.1112803],"study_design_scores_gemma":[0.001291917,0.00104903,0.7086076,0.0001002031,0.00002001242,0.00004834889,0.005596999,0.04049458,0.05735016,0.05029121,0.1342541,0.0008959158],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7970626,0.002874564,0.02121625,0.001124954,0.000424765,0.0003515064,6.417595e-7,0.0002538452,0.1766909],"genre_scores_gemma":[0.9978024,0.000009940057,0.001838368,0.00002446497,0.000071633,0.00001156289,2.685494e-7,0.000002313482,0.0002390735],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.726052,"threshold_uncertainty_score":0.1520399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01676542999552279,"score_gpt":0.2379658482056934,"score_spread":0.2212004182101707,"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."}}