{"id":"W2053469106","doi":"10.1080/1389224x.2012.670050","title":"Learning and Innovation Competence in Agricultural and Rural Development","year":2012,"lang":"en","type":"article","venue":"The Journal of Agricultural Education and Extension","topic":"Competency Development and Evaluation","field":"Psychology","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; University of Waterloo","funders":"International Development Research Centre","keywords":"Agricultural education; Competence (human resources); Business; Agriculture; Rural development; Agricultural development; Economic growth; Knowledge management; Marketing; Management; Geography; Economics; Computer science","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":[0.006932743,0.0001908517,0.0002590834,0.001402639,0.0007977635,0.002932908,0.000384661,0.0003739808,0.003157066],"category_scores_gemma":[0.01165627,0.00008481978,0.0001864911,0.0007202571,0.003677471,0.001563657,0.005923032,0.0008023179,0.0001899591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002121197,"about_ca_system_score_gemma":0.003590877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009212379,"about_ca_topic_score_gemma":0.001233212,"domain_scores_codex":[0.9961163,0.00249549,0.0001761201,0.0001863107,0.0007610066,0.0002647518],"domain_scores_gemma":[0.986925,0.008154459,0.001718799,0.000524282,0.001290118,0.001387312],"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":[0.0002623176,0.003246175,0.2923816,0.001696608,0.000102155,0.0006474474,0.07174993,0.007178427,0.005008693,0.1394074,0.00288364,0.4754358],"study_design_scores_gemma":[0.0001250621,0.002170939,0.5963989,0.002049687,0.00009408125,0.001567626,0.1003339,0.01427242,0.01308333,0.2129351,0.05680856,0.0001603445],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9106491,0.0006817938,0.006239665,0.001514567,0.00001871085,0.0001897894,0.00003763368,0.00002059958,0.08064821],"genre_scores_gemma":[0.9976399,0.0001515979,0.001404418,0.00004239924,0.00000373421,0.00003379247,0.000009187966,0.000001483546,0.000713554],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006932743,"threshold_uncertainty_score":0.03666431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02585205350254164,"score_gpt":0.3172688172221473,"score_spread":0.2914167637196056,"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."}}