{"id":"W4313472540","doi":"10.3390/land12010132","title":"The Global Land Rush and Agricultural Investment in Ghana: Existing Knowledge, Gaps, and Future Directions","year":2022,"lang":"en","type":"article","venue":"Land","topic":"Agriculture, Land Use, Rural Development","field":"Agricultural and Biological Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; University of Northern British Columbia","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Land grabbing; Agricultural land; Livelihood; Food security; Agriculture; Business; Scholarship; Scale (ratio); Investment (military); Economic growth; Natural resource economics; Environmental resource management; Geography; Political science; Economics; Politics","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":[0.002154932,0.0005362887,0.001016195,0.002383551,0.0008860957,0.004428689,0.0006703649,0.001577295,0.005650705],"category_scores_gemma":[0.004208152,0.0004876734,0.000477829,0.008131932,0.0040153,0.00692002,0.001685706,0.001637353,0.0004817737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003415376,"about_ca_system_score_gemma":0.007188112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02290384,"about_ca_topic_score_gemma":0.0360829,"domain_scores_codex":[0.999189,0.0003423072,0.00007844742,0.0001687982,0.0000979715,0.0001234336],"domain_scores_gemma":[0.992436,0.005593008,0.001194661,0.00008307379,0.0004459958,0.0002471849],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000133329,0.0001131505,0.03390966,0.05069693,0.0001447682,0.002081912,0.02537393,0.0007401315,0.0005960699,0.05240112,0.01972585,0.814083],"study_design_scores_gemma":[0.00002156098,0.0002063363,0.09366126,0.1041061,0.0003492995,0.002443601,0.1476786,0.0006939609,0.0004067203,0.0447925,0.6055347,0.0001052778],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01125527,0.9674933,0.0002566793,0.01604317,0.0002766805,0.00001378338,0.0002123662,0.000005630008,0.004443161],"genre_scores_gemma":[0.08681218,0.910127,0.0004561192,0.001887623,0.0002584534,0.00001750134,0.0001082684,0.00000505258,0.0003278091],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.02290384,"threshold_uncertainty_score":0.04554105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01324777964428747,"score_gpt":0.21955773723576,"score_spread":0.2063099575914726,"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."}}