{"id":"W1522067404","doi":"","title":"Gestão metropolitano no Canadá: um estudo de casos","year":2009,"lang":"pt","type":"article","venue":"Ensaios FEE","topic":"Urban Development and Societal Issues","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metropolitan area; Interdependence; Variety (cybernetics); Government (linguistics); Local government; Subject (documents); Focus (optics); Regional science; Geography; Political science; Sociology; Public administration; Library science; Computer science; Social science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"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":[0.0008492871,0.0003782064,0.0004774865,0.0001081823,0.001020518,0.0002467284,0.0006347211,0.0003758436,0.001860081],"category_scores_gemma":[0.0004107799,0.0003913444,0.0002400038,0.0006772504,0.0002919242,0.000276236,0.00006774601,0.0004076791,0.001985314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00118464,"about_ca_system_score_gemma":0.0008689681,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02019933,"about_ca_topic_score_gemma":0.01589247,"domain_scores_codex":[0.9965877,0.0003016274,0.0004107892,0.0005131966,0.0008473459,0.001339326],"domain_scores_gemma":[0.9985678,0.0001525436,0.0001576707,0.000341326,0.0002094295,0.0005712199],"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":[0.00003374866,0.0003591623,0.02322711,0.00003454522,0.0002669156,0.0002882878,0.1992532,0.000003571013,0.0007845835,0.02090816,0.7491328,0.005708017],"study_design_scores_gemma":[0.0007922996,0.0004358007,0.05632774,0.0001149552,0.0001876855,0.000007225251,0.0444096,0.00009382086,0.0008338325,0.002371134,0.8931082,0.00131765],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.625962,0.004128734,0.00002682051,0.01570085,0.002434165,0.0006329197,0.00002628211,0.0002942338,0.350794],"genre_scores_gemma":[0.7294222,0.0003421655,0.0004761526,0.001582083,0.0009505245,0.000006740339,0.000007605285,0.00002349354,0.267189],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1548436,"threshold_uncertainty_score":0.9998538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02891424173729302,"score_gpt":0.3073052204287076,"score_spread":0.2783909786914146,"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."}}