{"id":"W4238019513","doi":"10.32920/ryerson.14667897.v1","title":"The Spatial Distribution of Development Across Africa and Its Underlying Sustainability Correlations","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Sustainable Development and Environmental Policy","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Sustainability; Sustainable development; Distribution (mathematics); Spatial analysis; Geography; Natural resource; Socioeconomic status; Spatial distribution; Environmental resource management; Environmental planning; Political science; Economics; Population; Ecology","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":[0.0005461164,0.0002381009,0.0002112153,0.00001162358,0.0007320478,0.0001173186,0.000259379,0.0001817052,0.000265564],"category_scores_gemma":[0.0002097954,0.0001886427,0.00006279125,0.0001525012,0.0003348452,0.0001273157,0.003031758,0.0002942561,0.00001509194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001447687,"about_ca_system_score_gemma":0.0001875517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009588026,"about_ca_topic_score_gemma":0.0006104299,"domain_scores_codex":[0.9981516,0.00008205952,0.0004491283,0.0004599526,0.0003888113,0.0004684658],"domain_scores_gemma":[0.9992369,0.0001329874,0.0001866825,0.0003062004,0.00003247514,0.0001047321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001919586,0.0009922684,0.4724567,0.00118515,0.0004625655,0.00005457777,0.06470785,0.04102765,0.0007228645,0.002983599,0.003530892,0.4116839],"study_design_scores_gemma":[0.0001922464,0.00001400268,0.9738541,0.00002409039,0.00001836184,0.000002854319,0.01138068,0.002294843,0.0006731952,0.001904409,0.009313757,0.0003274913],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910131,0.0002254587,0.005412508,0.0005303727,0.0001475249,0.0005801392,0.00001651984,0.00002828548,0.002046145],"genre_scores_gemma":[0.9963554,0.0001021458,0.0002637802,0.00001446806,0.00001219639,0.00008880509,0.0001778095,0.00001248916,0.002972879],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5013974,"threshold_uncertainty_score":0.7692625,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02340547063114172,"score_gpt":0.2709320666610851,"score_spread":0.2475265960299434,"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."}}