{"id":"W320082670","doi":"10.4271/2006-01-0812","title":"NaviQ - A User Satisfaction Questionnaire for IVNS","year":2006,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"User satisfaction; Computer science; Human–computer interaction","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":[0.003013718,0.0002944039,0.0005312818,0.0008860776,0.0003110787,0.0005440704,0.0003278511,0.0003628664,0.006903629],"category_scores_gemma":[0.009170189,0.0001443752,0.0004698466,0.0006975254,0.0001875213,0.0007569931,0.0007023233,0.0005948342,0.00157352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003715299,"about_ca_system_score_gemma":0.0003195678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009412285,"about_ca_topic_score_gemma":0.001509865,"domain_scores_codex":[0.9978868,0.0009040307,0.0003426026,0.000134907,0.0005817133,0.0001499331],"domain_scores_gemma":[0.9918213,0.003621323,0.001099135,0.0004255893,0.002376997,0.0006556903],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001572465,0.003123971,0.6185398,0.0006869488,0.0001603168,0.0003454697,0.01488766,0.002265226,0.01319135,0.001434608,0.02982146,0.3139707],"study_design_scores_gemma":[0.0001125376,0.00524054,0.9354283,0.0001264199,0.00006333964,0.0005380363,0.008638666,0.009588083,0.004936643,0.0005584096,0.03464151,0.000127557],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9763257,0.00007377581,0.008053546,0.0002544912,0.00003561847,0.001426144,0.003281123,0.0004221394,0.01012744],"genre_scores_gemma":[0.9756614,0.0001141203,0.01167618,0.0002540977,0.00001674533,0.001943622,0.004087012,0.00008802,0.006158741],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006903629,"threshold_uncertainty_score":0.02309489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01488861034227157,"score_gpt":0.2575214291352863,"score_spread":0.2426328187930147,"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."}}