{"id":"W2971428932","doi":"10.33017/reveciperu2007.0004/","title":"LOS DESAFÍOS CONFRONTADOS POR LOS PROYECTOS CONVENCIONALES DE TRANSPORTE Y EL POTENCIAL DE LOS SISTEMAS INTELIGENTES DE TRANSPORTE PARA UNA CIUDAD EN DESARROLLO, LIMA, PERÚ","year":2019,"lang":"es","type":"article","venue":"Revista ECIPeru","topic":"Business, Innovation, and Economy","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Transports","funders":"","keywords":"Computer science; Business; Transport engineering; Engineering","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":[0.001808452,0.0002961891,0.0001592228,0.0006400708,0.003889624,0.004630984,0.0007347983,0.001393205,0.007689277],"category_scores_gemma":[0.005009053,0.0002586744,0.0002570908,0.001625147,0.002828122,0.003029965,0.003831865,0.00163676,0.0005168013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004341007,"about_ca_system_score_gemma":0.006993589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05622103,"about_ca_topic_score_gemma":0.07141998,"domain_scores_codex":[0.9985227,0.0007178811,0.00004803224,0.0001599826,0.0002599331,0.0002913426],"domain_scores_gemma":[0.9976686,0.0009578849,0.0003293758,0.00009600633,0.0006996106,0.0002486356],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003373211,0.0003522193,0.209716,0.002219643,0.0001452215,0.006678888,0.13056,0.005786282,0.009707459,0.2461393,0.06548583,0.3228719],"study_design_scores_gemma":[0.00003833537,0.0004206992,0.2986128,0.001189052,0.0001249305,0.001388869,0.1943464,0.004075284,0.002855254,0.0308357,0.4660019,0.0001106555],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.723206,0.009593772,0.006127825,0.1108413,0.0002096802,0.0002203459,0.0003520861,0.0001460881,0.1493029],"genre_scores_gemma":[0.9710565,0.006461111,0.001269501,0.001387405,0.00007537508,0.0001649603,0.0001489104,0.00002722908,0.01940902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05622103,"threshold_uncertainty_score":0.1117876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02219732072083326,"score_gpt":0.2493253788089572,"score_spread":0.2271280580881239,"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."}}