{"id":"W6938891713","doi":"10.6068/dp14ba8267cc40","title":"Most Recent Data (2011). Statistics Canada. CANSIM: Agriculture - Farms and Farm Operators | Country: Canada | Table: Socioeconomic overview of the farm population, farms with one or more operators by sources of income for farm households in the year prior to the census | Variable: All farms, $100,000 and over, Wages and salaries | Units: #, 2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-004.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Agriculture; Socioeconomic status; Economic statistics; Distribution (mathematics); Official statistics; Farm income; Summary statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002128828,0.002381387,0.002576812,0.007682265,0.003656094,0.004912056,0.004777872,0.001576574,0.1316989],"category_scores_gemma":[0.01901238,0.001687809,0.001922094,0.04301858,0.0006814932,0.002647034,0.002472893,0.002876679,0.07575924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05449899,"about_ca_system_score_gemma":0.1450592,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9948261,"about_ca_topic_score_gemma":0.9934152,"domain_scores_codex":[0.9953958,0.0002779161,0.0004717081,0.0005370824,0.002235883,0.001081606],"domain_scores_gemma":[0.9582763,0.001568176,0.001016363,0.001053259,0.03615665,0.001929198],"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":[0.00001639861,0.000005720887,0.0006911074,0.0001986716,0.00001227717,0.000005400757,0.00001933158,0.0000804374,0.00000755232,0.0002553574,0.9973872,0.001320348],"study_design_scores_gemma":[0.0001210982,0.00001083256,0.02096948,0.0007672539,0.0000548048,0.00002269665,0.0005114696,0.0003477213,0.0001434711,0.0005513034,0.9764156,0.00008426937],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000455966,0.00004516856,0.00002013643,0.0001310132,0.00002383134,0.00001319359,0.9985015,0.00005328347,0.001166205],"genre_scores_gemma":[0.0008193018,0.0003243419,0.0004222614,0.0002202944,0.00001822948,0.0001189123,0.9921982,0.0001271069,0.005751338],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1316989,"threshold_uncertainty_score":0.4405768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03121308431822647,"score_gpt":0.2555546699469758,"score_spread":0.2243415856287493,"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."}}