{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009061687,0.0008105651,0.0009549874,0.0003312936,0.0006735548,0.0004467092,0.001456435,0.0008711317,0.0001241704],"category_scores_gemma":[0.0006874956,0.0007575313,0.0006649585,0.001069647,0.0005458503,0.001892842,0.0004886409,0.000944317,0.0002581945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00058854,"about_ca_system_score_gemma":0.0001934352,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005172797,"about_ca_topic_score_gemma":0.2251382,"domain_scores_codex":[0.9945329,0.0002769882,0.001279683,0.001758249,0.001095531,0.001056632],"domain_scores_gemma":[0.9961788,0.0008268663,0.0004185287,0.001896922,0.0003394412,0.0003394575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001407593,0.0003665181,0.001273963,0.00006681708,0.00003810128,0.00002877068,0.00002331507,0.00001141858,0.8863232,0.06958957,0.01052294,0.03161469],"study_design_scores_gemma":[0.0009090926,0.0008708741,0.9046265,0.0003190743,0.00004541444,0.0002216747,0.00002452683,6.867327e-7,0.0002427425,0.009797282,0.08213503,0.0008070265],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8005551,0.001694164,0.006621617,0.05134368,0.005187002,0.01301408,0.0005200908,0.03373818,0.0873261],"genre_scores_gemma":[0.9863696,0.00004516724,0.009224245,0.001531417,0.0004117373,0.001268442,0.00004622621,0.0001075833,0.0009956176],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9033526,"threshold_uncertainty_score":0.9994876,"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."}}