{"id":"W1483427682","doi":"10.4000/bifea.5857","title":"Innovaciones tecnológicas aplicadas al transporte colectivo en Quito. Optimización en la evaluación de la demanda con GPS y SIG","year":2004,"lang":"es","type":"article","venue":"Bulletin de l’Institut français d’études andines","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Transports","funders":"","keywords":"Global Positioning System; Geography; Transport engineering; Cartography; Welfare economics; Humanities; Forestry; Computer science; Engineering; Telecommunications; Economics; Art","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","sts"],"consensus_categories":[],"category_scores_codex":[0.002619382,0.0007031661,0.0007865643,0.0003586566,0.001373674,0.0005482905,0.000695299,0.001062165,0.0008061687],"category_scores_gemma":[0.0005060955,0.0007046677,0.0003309058,0.00101927,0.001169462,0.000283113,0.00003911355,0.0008063592,0.0001233626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003100945,"about_ca_system_score_gemma":0.001045874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005103421,"about_ca_topic_score_gemma":0.001097248,"domain_scores_codex":[0.9954171,0.000799019,0.0009299036,0.0009187881,0.0009455732,0.000989583],"domain_scores_gemma":[0.9975213,0.001031141,0.0003547699,0.0003755945,0.0003164413,0.0004007942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001461662,0.002332743,0.1022994,0.000694807,0.0007643984,0.0009842662,0.07940654,0.5292611,0.002641843,0.2673609,0.007966513,0.004825857],"study_design_scores_gemma":[0.005160269,0.0003143746,0.06275933,0.0008322629,0.0004710954,0.0001125941,0.003187027,0.0006897714,0.0006954059,0.0004726679,0.9241522,0.00115303],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8611897,0.002581309,0.04302127,0.03756534,0.001000804,0.002038348,0.0003708052,0.001134214,0.05109819],"genre_scores_gemma":[0.9822751,0.005411731,0.009780201,0.0009183498,0.0006024222,0.000167688,0.0001498207,0.00008979066,0.0006049197],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9161857,"threshold_uncertainty_score":0.9999264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009208003723731808,"score_gpt":0.2953481582295056,"score_spread":0.2861401545057737,"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."}}