{"id":"W2995074539","doi":"10.1007/s12132-019-09382-4","title":"Improving Land Tenure Administration Effectiveness in a Post-Conflict Peri-Urban Mombasa Settlement","year":2019,"lang":"en","type":"article","venue":"Urban Forum","topic":"Land Rights and Reforms","field":"Agricultural and Biological Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Natural Resources Canada; University of Calgary","funders":"","keywords":"Settlement (finance); Land administration; Politics; Land tenure; Context (archaeology); Administration (probate law); Government (linguistics); Economic growth; Political science; Social conflict; Land use; Geography; Environmental planning; Business; Economics; Law; Agriculture; Civil engineering","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":[0.0001580625,0.00012211,0.0001465929,0.00001321502,0.0001009476,0.00005734882,0.0001019846,0.00009718619,0.0002061574],"category_scores_gemma":[0.000005893882,0.00002487515,0.00006655925,0.0001112565,0.0000191148,0.0001257818,0.00003858072,0.0001000513,0.00005596357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003612865,"about_ca_system_score_gemma":0.00001503073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005410429,"about_ca_topic_score_gemma":0.001561941,"domain_scores_codex":[0.999164,0.00003383274,0.0001457186,0.0002380045,0.0001301749,0.0002882124],"domain_scores_gemma":[0.9997638,0.00003867119,0.00005570826,0.00005400817,0.00002897661,0.00005882739],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001700516,0.000152537,0.8695705,0.00004402553,0.00001859513,0.00001657361,0.0002439005,0.000003444613,0.102801,0.0004726803,0.0005296565,0.02597706],"study_design_scores_gemma":[0.0005996553,0.001161402,0.8859622,0.00005309244,0.00000739851,0.00001076596,0.0003495271,0.0001861556,0.006023759,0.0001191116,0.1052657,0.0002611401],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997046,0.00007513654,8.926637e-7,0.00144305,0.0002139341,0.0004054527,0.00006585131,0.00003197723,0.0007176872],"genre_scores_gemma":[0.9968476,0.0000069303,0.000005559434,0.0001524632,0.0001317565,0.00001595977,0.0001799143,0.000001190674,0.002658586],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1047361,"threshold_uncertainty_score":0.2257279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00658403492620525,"score_gpt":0.1991901354159179,"score_spread":0.1926061004897126,"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."}}