{"id":"W2955649334","doi":"10.1007/s10479-019-03295-y","title":"Goal programming approach for political districting in Santa Catarina State: Brazil","year":2019,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Optimization and Mathematical Programming","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Transport Canada","funders":"","keywords":"Contiguity; Legislation; Redistricting; Politics; Context (archaeology); Population; State (computer science); Distribution (mathematics); Public administration; Operations research; Computer science; Political science; Economics; Sociology; Geography; Mathematics; Law; Demography","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":[],"consensus_categories":[],"category_scores_codex":[0.0008664749,0.00008209429,0.0001614059,0.0002216854,0.00008390315,0.0001077347,0.0001569208,0.0000548069,0.00003271209],"category_scores_gemma":[0.0003390131,0.0000789179,0.00004457312,0.0004828384,0.00005934466,0.0001998604,0.0000503489,0.0002288979,0.000016177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003226721,"about_ca_system_score_gemma":0.00005171306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001046618,"about_ca_topic_score_gemma":0.00003171976,"domain_scores_codex":[0.9986905,0.00004645834,0.000308301,0.0001596399,0.0002565278,0.0005385789],"domain_scores_gemma":[0.9992497,0.0001844457,0.000007055519,0.0001860413,0.0002677005,0.0001050352],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007058042,0.001241059,0.004183513,0.002868309,0.0001095176,0.000004265264,0.002663564,0.6690401,0.003532345,0.2485284,0.001976135,0.06578225],"study_design_scores_gemma":[0.000372468,0.0001269647,0.000244567,0.00004742693,0.00000215686,0.000002056881,0.001098844,0.9919147,0.003691329,0.0004532556,0.0018973,0.0001488958],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6488236,0.0003638233,0.3187991,0.0009154297,0.0001082051,0.004107918,0.00007273311,0.0002359457,0.02657325],"genre_scores_gemma":[0.958575,0.00002318026,0.04082274,0.00001595197,0.00002300673,0.0001628418,0.00007197878,0.00002259534,0.000282709],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3228746,"threshold_uncertainty_score":0.3218178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1175610617933781,"score_gpt":0.4274436727247257,"score_spread":0.3098826109313476,"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."}}