{"id":"W3084735341","doi":"10.1111/ecog.05205","title":"Drivers of global variation in land ownership","year":2020,"lang":"en","type":"article","venue":"Ecography","topic":"Rangeland Management and Livestock Ecology","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; McGill University","funders":"","keywords":"Land tenure; Subsistence agriculture; Territoriality; Population; Land use; Natural resource; Ecology; Natural resource economics; Environmental resource management; Economics; Geography; Sociology; Biology; Agriculture; 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":[0.00004807031,0.00003567603,0.00005720811,0.00001438744,0.00001128014,0.000002737711,0.00007567312,0.00002267579,0.0007354276],"category_scores_gemma":[0.000007037509,0.00003208407,0.00002797778,0.0003336583,0.00003199309,0.00006116075,0.00003662277,0.00002389592,0.00007315247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001158931,"about_ca_system_score_gemma":0.000001138557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001568936,"about_ca_topic_score_gemma":0.0005309705,"domain_scores_codex":[0.9996723,0.00001923796,0.0000702059,0.0001008288,0.00005713573,0.00008032666],"domain_scores_gemma":[0.9998884,0.000007993729,0.00003034731,0.00004206017,8.669611e-7,0.00003034189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009499182,0.00001568742,0.9973469,0.000002914785,0.000004924269,0.000001579225,0.0001959129,0.0002428351,0.00007598702,0.0003148572,0.001311785,0.000477167],"study_design_scores_gemma":[0.0002570971,0.00005601338,0.9959131,8.995821e-7,0.000004851465,7.364908e-8,0.00002869369,0.0002078848,0.000006123023,0.0007365304,0.002751358,0.00003739039],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9713475,0.000006010754,0.0001932407,0.0006596025,0.00003952122,0.00007944553,0.000002206328,0.00001090154,0.02766165],"genre_scores_gemma":[0.9995245,0.000005052331,0.0002903274,0.0001497047,0.00001090721,0.000002765492,0.000001789906,0.000001360664,0.00001357881],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02817709,"threshold_uncertainty_score":0.8052417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008100597186716189,"score_gpt":0.1906544237803283,"score_spread":0.1825538265936121,"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."}}