{"id":"W2281640194","doi":"10.22004/ag.econ.310731","title":"Evaluating Capacity Development in Planning, Monitoring, and Evaluation: A Case from Agricultural Research","year":2000,"lang":"en","type":"book","venue":"AgEcon Search (University of Minnesota, USA)","topic":"Agricultural Innovations and Practices","field":"Agricultural and Biological Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Danish International Development Agency; International Fund for Agricultural Development; Australian Centre for International Agricultural Research; Ministerie van Buitenlandse Zaken; Concordia University; Direktion für Entwicklung und Zusammenarbeit; International Development Research Centre","keywords":"Agriculture; Capacity development; Monitoring and evaluation; Environmental planning; Agricultural development; Business; Environmental resource management; Environmental science; Geography; Economics; Economic growth","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0027338,0.0002650333,0.0003978369,0.0001230226,0.0008329673,0.0001020799,0.0003979014,0.0003873421,0.004097118],"category_scores_gemma":[0.00008792273,0.000141454,0.00007316074,0.000584832,0.0002580899,0.0005817668,0.0002663997,0.0009250871,0.00009025184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003490039,"about_ca_system_score_gemma":0.0001722192,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007767411,"about_ca_topic_score_gemma":0.006949353,"domain_scores_codex":[0.9967679,0.0006728566,0.0003336842,0.000655178,0.001129864,0.0004404752],"domain_scores_gemma":[0.9974955,0.001188821,0.0002466667,0.0001089299,0.0008088045,0.0001512333],"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":[0.000418752,0.0005056452,0.01722327,0.000227441,0.0005062319,0.002288541,0.03159708,0.0001984781,0.02950907,0.0003267409,0.02958275,0.887616],"study_design_scores_gemma":[0.001122558,0.0006620896,0.8200138,0.001034488,0.0001314109,0.000284458,0.02724321,0.0003299428,0.0005518976,0.0005613546,0.1470225,0.001042288],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.969563,0.000680454,1.764024e-7,0.0003688115,0.00006006766,0.0006169844,0.0001110184,0.00001716884,0.02858234],"genre_scores_gemma":[0.8832171,0.0003852004,0.001753775,0.00001121551,0.000455979,0.000008192437,0.0007697971,0.000003683386,0.1133951],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8865737,"threshold_uncertainty_score":0.99884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3308207885326843,"score_gpt":0.3763393152432594,"score_spread":0.04551852671057505,"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."}}