{"id":"W4403572556","doi":"10.1016/j.landurbplan.2024.105231","title":"Using the Gini Index to quantify urban green inequality: A systematic review and recommended reporting standards","year":2024,"lang":"en","type":"review","venue":"Landscape and Urban Planning","topic":"Urban Green Space and Health","field":"Environmental Science","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Index (typography); Inequality; Gini coefficient; Geography; Mathematics; Economic inequality; 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"],"consensus_categories":[],"category_scores_codex":[0.004060156,0.0005587725,0.002672618,0.0001312021,0.0003612907,0.0002250103,0.0002966674,0.0002205576,0.00008202305],"category_scores_gemma":[0.0003386694,0.000322776,0.0002123488,0.0006332185,0.0000538675,0.0001346909,0.0005298233,0.0007179092,0.00003168724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001820435,"about_ca_system_score_gemma":0.0001096157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002488578,"about_ca_topic_score_gemma":0.00008837577,"domain_scores_codex":[0.9958987,0.0003784111,0.00187099,0.0007710498,0.0005483828,0.0005324483],"domain_scores_gemma":[0.9974145,0.0002351951,0.001436872,0.0006182297,0.00001899317,0.0002761635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005814598,0.00001221573,0.07943103,0.853308,0.0002446348,0.0001348077,0.001889619,9.884839e-7,1.734665e-7,0.0000314069,0.06098012,0.003961185],"study_design_scores_gemma":[0.0000969,0.00007875008,0.0001116588,0.4222508,0.004898344,0.0004290517,0.0002807595,0.0001930417,2.194825e-8,0.0000229933,0.5710341,0.0006035509],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001090639,0.9965805,0.00009355805,0.0004270194,0.0001171928,0.001941686,0.00009247456,0.00007176249,0.0005666916],"genre_scores_gemma":[0.0002886902,0.9966488,0.0001433264,0.001346939,0.0001828493,0.0001217643,0.00003658603,0.00007844606,0.001152526],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.5100541,"threshold_uncertainty_score":0.9999225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.129223849111915,"score_gpt":0.4067819930483123,"score_spread":0.2775581439363973,"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."}}