{"id":"W3095472749","doi":"10.33262/concienciadigital.v3i3.1355","title":"Estudio de factibilidad del uso de modelos de redes neuronales artificiales en la automatización del aforo y clasificación vehicular del transporte público","year":2020,"lang":"es","type":"article","venue":"ConcienciaDigital","topic":"Multidisciplinary Research Papers Compilation","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Philosophy","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":[0.001554498,0.000854736,0.0006410399,0.0005283454,0.0003718896,0.001601659,0.0008357562,0.001044542,0.002047771],"category_scores_gemma":[0.008564001,0.0004282887,0.0007998374,0.0004404903,0.0006662605,0.001442221,0.0006443181,0.001067871,0.0003125467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001338935,"about_ca_system_score_gemma":0.0007206848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01276151,"about_ca_topic_score_gemma":0.005124081,"domain_scores_codex":[0.9995722,0.0001538889,0.00002771902,0.0001025617,0.00009895645,0.00004471139],"domain_scores_gemma":[0.9972305,0.001813596,0.0001925257,0.0001761003,0.0005273622,0.00005993841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001257416,0.00005466021,0.002194823,0.0001329203,0.00006926337,0.00006271942,0.00007880534,0.961913,0.003734242,0.005498271,0.0004610419,0.02567448],"study_design_scores_gemma":[0.000005335184,0.00004018857,0.0003699271,0.00001081819,0.00001566702,0.00001134015,0.00001674742,0.9966872,0.0008160504,0.001666717,0.0003549235,0.000004991959],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3194786,0.002552947,0.6617128,0.001110599,0.0003058398,0.0001057265,0.0002936034,0.0009565614,0.01348339],"genre_scores_gemma":[0.9733439,0.000706244,0.02299412,0.00007682428,0.00002716691,0.00007508445,0.0001342844,0.0000492896,0.002593056],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01276151,"threshold_uncertainty_score":0.02537447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05850812054080599,"score_gpt":0.3412832288213402,"score_spread":0.2827751082805341,"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."}}