{"id":"W3027745686","doi":"10.3390/land9050167","title":"The Rush for Land and Agricultural Investment in Ethiopia: What We Know and What We Are Missing","year":2020,"lang":"en","type":"article","venue":"Land","topic":"Agriculture, Land Use, Rural Development","field":"Agricultural and Biological Sciences","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Agriculture; Government (linguistics); Agricultural land; Investment (military); Land use; Business; Geography; Environmental resource management; Natural resource economics; Environmental planning; Political science; Economics; Politics; 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":[0.0001343658,0.0001905185,0.0002157702,0.000004790798,0.0003371195,0.0009372106,0.000132352,0.0001161643,0.000008309579],"category_scores_gemma":[0.00004092264,0.00004956465,0.0000385293,0.0001642436,0.00005320726,0.0005565147,0.0001059391,0.0001431034,0.000004004329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002015688,"about_ca_system_score_gemma":0.000005324069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006018543,"about_ca_topic_score_gemma":0.003185168,"domain_scores_codex":[0.9989766,0.00005738464,0.0002004271,0.000319111,0.0001499402,0.0002965033],"domain_scores_gemma":[0.9993918,0.0002762957,0.00008669719,0.00003087217,0.00003749089,0.0001768449],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002383853,0.00008705872,0.3264673,0.0001892071,0.00008712354,0.00002672295,0.00551184,0.000008464497,0.004198881,0.0008896546,0.009706728,0.6525887],"study_design_scores_gemma":[0.000618707,0.0001661589,0.8010133,0.0004543454,0.00001755471,0.00001438705,0.007921284,0.00005760604,0.000383454,0.003484946,0.1855578,0.0003104113],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9016405,0.0311116,4.679298e-7,0.06662794,0.0001393055,0.0004112379,0.000009961879,0.00003038813,0.00002853443],"genre_scores_gemma":[0.8892879,0.1050047,0.000216551,0.004149124,0.0006483984,0.00009570438,0.0001010693,0.00000316754,0.0004934194],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6522782,"threshold_uncertainty_score":0.9037544,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02551516361410482,"score_gpt":0.2158178707459277,"score_spread":0.1903027071318229,"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."}}