{"id":"W6963876969","doi":"10.25318/3210009501-eng","title":"Average net market income of farms, by income quintile","year":2019,"lang":"en","type":"dataset","venue":"Statistics Canada Dissemination","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Net income; Adjusted gross income; Net national income; Comprehensive income; Income distribution; Distribution (mathematics); Gross income; Permanent income hypothesis","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":[0.0007854264,0.001036604,0.001134843,0.004365674,0.001046896,0.001859621,0.002080993,0.0007140465,0.03793515],"category_scores_gemma":[0.005877596,0.0006074324,0.0008380126,0.01216647,0.0003190965,0.001078105,0.001024855,0.001570719,0.0173277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007446832,"about_ca_system_score_gemma":0.01323959,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8413568,"about_ca_topic_score_gemma":0.8678033,"domain_scores_codex":[0.9988392,0.0000772376,0.0001372049,0.0002009859,0.0004417339,0.0003036609],"domain_scores_gemma":[0.9950766,0.0003870492,0.0005513862,0.000226271,0.00336787,0.0003908557],"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":[0.00004225344,0.00001214704,0.004587892,0.0002745484,0.00003098278,0.00001338912,0.00002074541,0.00021606,0.00002116396,0.000588314,0.9925372,0.001655405],"study_design_scores_gemma":[0.0002613361,0.00002476109,0.1405647,0.0006989447,0.00009393818,0.00008218249,0.0005146649,0.0009036717,0.0002944028,0.0007851217,0.8557127,0.00006359698],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003917144,0.00005479013,0.00003056457,0.00006653427,0.00001616803,0.00001289964,0.9982771,0.00003262623,0.001117683],"genre_scores_gemma":[0.002944289,0.000183859,0.0001903869,0.0000655871,0.00001359565,0.0000767382,0.9924887,0.00002739945,0.004009418],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1586432,"threshold_uncertainty_score":0.319155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004366654105388324,"score_gpt":0.2512455142302127,"score_spread":0.2468788601248244,"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."}}