{"id":"W128748169","doi":"","title":"Koordination multimodaler Metainformationen bei Fahrerinformationssystemen am Beispiel der Menüausgabe","year":2002,"lang":"de","type":"article","venue":"Ingénierie des systèmes d information","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Variety (cybernetics); Prime (order theory); Computer science; Mode (computer interface); Component (thermodynamics); Human–computer interaction; Multimedia; Artificial intelligence; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002762597,0.0008916049,0.0006225951,0.001001082,0.0007578008,0.002389001,0.0005666928,0.001511017,0.002871268],"category_scores_gemma":[0.008887348,0.0004335765,0.000396203,0.00058187,0.001267445,0.002863257,0.001519953,0.0007901739,0.0006468592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004523562,"about_ca_system_score_gemma":0.0002646304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005075188,"about_ca_topic_score_gemma":0.0006524601,"domain_scores_codex":[0.997867,0.001008345,0.0001105485,0.0002202698,0.0006257507,0.0001681889],"domain_scores_gemma":[0.9943486,0.004217017,0.0003086671,0.0004810471,0.0005256046,0.0001190792],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00446709,0.000568177,0.009627214,0.001297692,0.0002245386,0.006732007,0.01398124,0.03628381,0.5830965,0.01600003,0.001049062,0.3266726],"study_design_scores_gemma":[0.000276335,0.00483216,0.0249767,0.0003097448,0.000588246,0.01008898,0.006662876,0.2912554,0.6045181,0.03426646,0.02182347,0.0004015447],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8126916,0.001217724,0.1789633,0.0002438571,0.00003490652,0.0001567538,0.00008191451,0.001843589,0.004766365],"genre_scores_gemma":[0.959918,0.0002546685,0.03821821,0.00003374002,0.000009812145,0.00006492787,0.00006555879,0.0001258746,0.001309196],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002871268,"threshold_uncertainty_score":0.01461023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02367242621558145,"score_gpt":0.2277505807699949,"score_spread":0.2040781545544135,"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."}}