{"id":"W4409675387","doi":"10.1177/00307270251335671","title":"Towards a theory of agrarian skilling (Or, why farmer knowledge does not stop at the edge of the field)","year":2025,"lang":"en","type":"article","venue":"Outlook on Agriculture","topic":"Agriculture, Land Use, Rural Development","field":"Agricultural and Biological Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Agrarian society; Field (mathematics); Enhanced Data Rates for GSM Evolution; Business; Agroforestry; Agricultural engineering; Agricultural economics; Geography; Economics; Agriculture; Mathematics; Environmental science; Computer science; Engineering; Archaeology; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003666176,0.0003240041,0.0003808619,0.0000152043,0.0004473437,0.00004232412,0.0008968382,0.0002816484,0.00050936],"category_scores_gemma":[0.0002299908,0.00005435475,0.0003415706,0.0007858337,0.000132153,0.00006171624,0.0003906675,0.0003352644,0.00002646582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006216633,"about_ca_system_score_gemma":0.00003554368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001383546,"about_ca_topic_score_gemma":0.002331613,"domain_scores_codex":[0.9981829,0.0002724699,0.0004406713,0.0003902676,0.0003738138,0.00033991],"domain_scores_gemma":[0.9985095,0.0007454618,0.000265117,0.0001933578,0.0002182628,0.00006825951],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007497422,0.0008253798,0.007480522,0.0001684029,0.0004507907,0.000005726856,0.004103787,0.00003131721,0.1199465,0.06518192,0.7015935,0.09946243],"study_design_scores_gemma":[0.0004229801,0.0002285767,0.2866095,0.0004008415,0.000127797,0.000006004079,0.003339936,0.000001903195,0.3225638,0.004838497,0.3810503,0.0004098699],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9540985,0.0007710531,0.00000851913,0.01453832,0.001128877,0.0009359263,0.0001939349,0.00006982614,0.02825501],"genre_scores_gemma":[0.9340152,0.0001613125,0.00002564686,0.00381223,0.000235254,0.00005371827,0.0000517456,0.000001559805,0.06164335],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3205432,"threshold_uncertainty_score":0.5577135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01167848369319235,"score_gpt":0.2288184368346061,"score_spread":0.2171399531414138,"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."}}