{"id":"W4389841736","doi":"10.56083/rcv3n12-190","title":"BOT TELEGRAM PARA MAPEAMENTO DE RUAS PERIGOSAS","year":2023,"lang":"pt","type":"article","venue":"Revista Contemporânea","topic":"Urban Development and Societal Issues","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Transports","funders":"","keywords":"Political science; Business; Computer science","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":[0.0005778887,0.0008451903,0.0004786006,0.001249985,0.0008967239,0.001651546,0.001021501,0.001296764,0.01242494],"category_scores_gemma":[0.00227371,0.0003212689,0.0004292658,0.000910109,0.0005569342,0.001911093,0.002094944,0.0007375404,0.00344369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004875687,"about_ca_system_score_gemma":0.0008000382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004924926,"about_ca_topic_score_gemma":0.007592625,"domain_scores_codex":[0.9993994,0.0001519155,0.00002074311,0.0001259811,0.0002117632,0.00009019576],"domain_scores_gemma":[0.998518,0.0006287384,0.0001126226,0.0002843601,0.000296774,0.0001595125],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001723728,0.0004906271,0.01355525,0.001992276,0.0000979262,0.004294428,0.01036682,0.01131881,0.1440533,0.0161509,0.03991884,0.7560372],"study_design_scores_gemma":[0.0003030551,0.002607375,0.06121292,0.001141134,0.0004953601,0.006101593,0.0218026,0.2334641,0.1036846,0.01711535,0.5516998,0.0003721103],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3023747,0.003058549,0.573257,0.002045185,0.001108819,0.001138284,0.002024626,0.03129117,0.08370169],"genre_scores_gemma":[0.7942355,0.001327387,0.1345693,0.0005253028,0.0001289448,0.0005390359,0.001071027,0.0008313178,0.0667722],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01242494,"threshold_uncertainty_score":0.0415656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1018663987441447,"score_gpt":0.3644497469404276,"score_spread":0.262583348196283,"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."}}