{"id":"W2998727043","doi":"10.31124/advance.11472261.v2","title":"Women's Tenure Rights and Land Reform in Angola","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Land Rights and Reforms","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"European Commission; International Development Research Centre; World Bank Group","keywords":"Land tenure; Livelihood; Human settlement; Inheritance (genetic algorithm); Legislation; Business; Government (linguistics); Security of tenure; Land law; Population; Economic growth; Customary land; Property rights; Development economics; Political science; Geography; Economics; Agriculture; Law; Sociology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001831702,0.0001153781,0.00018157,0.0006810699,0.006488334,0.005799829,0.0005787958,0.0009631283,0.006817885],"category_scores_gemma":[0.002838427,0.0001915809,0.00009446702,0.0009411523,0.006574266,0.002509582,0.002897076,0.00137907,0.0004053111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007198162,"about_ca_system_score_gemma":0.004156364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04250706,"about_ca_topic_score_gemma":0.08690352,"domain_scores_codex":[0.9984162,0.0005670865,0.00003095864,0.00007278623,0.00009261451,0.0008203959],"domain_scores_gemma":[0.9988952,0.0003898806,0.0002093521,0.00004350096,0.000118057,0.0003441125],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002131987,0.0002884543,0.04071354,0.0002182791,0.00001709765,0.001650052,0.2359814,0.0003338152,0.001194837,0.6098517,0.01103732,0.0985003],"study_design_scores_gemma":[0.00007557245,0.0002456235,0.08079021,0.0009633935,0.00002325003,0.0005379799,0.3924886,0.0004926604,0.00108863,0.06064754,0.4625877,0.00005883002],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7704806,0.007607753,0.0003664007,0.02065838,0.0001520355,0.00005026308,0.00005361832,0.000009967501,0.200621],"genre_scores_gemma":[0.9769784,0.001383697,0.0001118354,0.0007467823,0.00004350199,0.00001750625,0.00001944051,0.000005073421,0.02069371],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04250706,"threshold_uncertainty_score":0.08451927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01653580842983009,"score_gpt":0.2012034998725152,"score_spread":0.1846676914426851,"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."}}