{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002658651,0.0004967491,0.0007846912,0.0001622181,0.001104378,0.0009920897,0.0008331006,0.0003995128,0.001162964],"category_scores_gemma":[0.0003933737,0.0005046816,0.0004936844,0.001624043,0.0005083112,0.0003986304,0.0002365748,0.0004282715,0.004599018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004890229,"about_ca_system_score_gemma":0.0007930562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001261341,"about_ca_topic_score_gemma":0.0002733961,"domain_scores_codex":[0.99548,0.0006080293,0.0008000646,0.0007431955,0.0009916886,0.001377015],"domain_scores_gemma":[0.9981388,0.0003024777,0.0003274922,0.0005042322,0.0001667485,0.0005602149],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004921091,0.0002032841,0.05744927,0.0004085069,0.0004086965,0.0003180951,0.1384198,0.000001199118,0.0005707545,0.02128085,0.7737479,0.007142488],"study_design_scores_gemma":[0.000441065,0.00008633557,0.006940977,0.0003011203,0.00007386459,0.000002035548,0.0287557,0.0001341524,0.0000601392,0.0002662312,0.9622828,0.0006555738],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7875336,0.02788476,0.0001569706,0.0266521,0.002627229,0.003019533,0.0001381977,0.002171681,0.1498159],"genre_scores_gemma":[0.562636,0.002784487,0.0000728021,0.0004110477,0.0005298367,0.00005865267,0.00006865179,0.00005155102,0.4333869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.283571,"threshold_uncertainty_score":0.9997501,"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."}}