{"id":"W1990783434","doi":"10.1016/s0959-3780(03)00050-5","title":"Introduction to an academic programme designed to meet the human capacity needs of drylands","year":2003,"lang":"en","type":"article","venue":"Global Environmental Change","topic":"Agriculture and Rural Development Research","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"United Nations University Institute for Water, Environment, and Health; McMaster University","funders":"","keywords":"Capacity building; Capacity development; Business; Environmental resource management; Environmental science; Economic growth; Economics","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":[0.00029933,0.0001352095,0.0001214892,0.000009869367,0.0002224177,0.0000212743,0.0002698262,0.00009346627,0.0004550891],"category_scores_gemma":[0.00001449861,0.00004311767,0.00004448086,0.0004521485,0.00006389491,0.0001181504,0.00008404711,0.00008146862,0.0000825585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001249188,"about_ca_system_score_gemma":0.00000195105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002691426,"about_ca_topic_score_gemma":0.0002587798,"domain_scores_codex":[0.9988452,0.0001051649,0.0001577657,0.0002126957,0.0003155883,0.0003636038],"domain_scores_gemma":[0.9996538,0.00001084147,0.00003991721,0.00006772287,0.000008579243,0.0002191207],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00003652878,0.000222683,0.06054857,0.000004979567,0.00001896038,0.000001111363,0.001193087,0.000002903371,0.8880711,0.004731326,0.01277106,0.03239771],"study_design_scores_gemma":[0.0001642436,0.001299622,0.8322012,0.00001058436,0.00001567273,0.00001909212,0.003801512,7.328426e-7,0.04118337,0.0007350868,0.1202378,0.0003310671],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917566,0.00004646831,0.000003419644,0.006741677,0.0000693607,0.0006649799,0.00004516295,0.00002237124,0.0006499587],"genre_scores_gemma":[0.9984741,0.00001320771,0.00007940213,0.0004737986,0.0005244643,0.0000984998,0.00005641345,7.480082e-7,0.0002793593],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8468877,"threshold_uncertainty_score":0.4982907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04737933270857442,"score_gpt":0.2506072787840863,"score_spread":0.2032279460755119,"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."}}