{"id":"W1590017995","doi":"10.22004/ag.econ.122234","title":"The impact of management skills on farm incomes in Canada","year":2007,"lang":"en","type":"article","venue":"AgEcon Search (University of Minnesota, USA)","topic":"Banking, Crisis Management, COVID-19 Impact","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Hectare; Subsidy; Revenue; Agricultural economics; Net farm income; Business; Farm income; Agriculture; Depreciation (economics); Economics; Stock (firearms); Labour economics; Production (economics); Agricultural science; Finance; Capital formation; Economic growth; Market economy; Financial capital; Human capital; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009616461,0.0001349149,0.0002183421,0.00008081166,0.0002059052,0.00001611439,0.0007276472,0.00004408972,0.0003086339],"category_scores_gemma":[0.00002944903,0.00006297773,0.0001320503,0.0006504524,0.0001236496,0.00009637212,0.0002630078,0.0001492327,0.00001533639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006619794,"about_ca_system_score_gemma":0.00008082234,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9026648,"about_ca_topic_score_gemma":0.9785025,"domain_scores_codex":[0.99855,0.00009657344,0.0001808266,0.0002458456,0.0004505863,0.0004761639],"domain_scores_gemma":[0.9989298,0.0005905495,0.0001508182,0.000153619,0.00006060216,0.0001146079],"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":[0.0002655066,0.0002221761,0.3402428,0.0000369242,0.0001845817,0.0002231475,0.0005613729,0.0004079155,0.00308697,0.0008990205,0.002707207,0.6511623],"study_design_scores_gemma":[0.0003169451,0.0002105166,0.9888637,0.00002467641,0.000008871956,7.837267e-7,0.005619453,0.00009267849,0.0002540316,0.00007771199,0.004414417,0.000116195],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935316,0.00002549481,0.00001307646,0.0008270251,0.00004198939,0.000284666,0.00003467352,0.000007614908,0.005233802],"genre_scores_gemma":[0.9990658,0.0001770695,0.00002981089,0.00006655631,0.00001497186,1.978789e-7,0.000009114186,0.000001086997,0.0006354381],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6510462,"threshold_uncertainty_score":0.3379324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01548087295413379,"score_gpt":0.242778719204617,"score_spread":0.2272978462504832,"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."}}