{"id":"W6901687543","doi":"10.6068/dp14ba7f9d40485","title":"Trend 1965 - 1970. Statistics Canada. CANSIM: Agriculture - Farm Financial Statistics | Country: Canada | Table: Total cash receipts from farming operations | Variable: Dairy supplementary payments | Units: $CAD x 1,000, 1965-1970. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-003.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Descriptive statistics; Economic statistics; Cash; Census; Revenue; Payment; Summary statistics; Official 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":[0.002074414,0.002138587,0.002280211,0.009728558,0.003302359,0.004574511,0.004275961,0.001259508,0.1075011],"category_scores_gemma":[0.01583298,0.001705844,0.001802517,0.04314481,0.0006386525,0.002430281,0.002123105,0.002752035,0.05862236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05920252,"about_ca_system_score_gemma":0.1590875,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.995587,"about_ca_topic_score_gemma":0.9933508,"domain_scores_codex":[0.995685,0.0002351551,0.0004085162,0.0005103629,0.00211533,0.001045555],"domain_scores_gemma":[0.9657683,0.001115602,0.001010153,0.0009297223,0.02958136,0.001594905],"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":[0.00002371976,0.000006268243,0.001033151,0.000249396,0.00001840908,0.000007982173,0.00002592096,0.0001099631,0.00001237839,0.0005344386,0.9956897,0.002288736],"study_design_scores_gemma":[0.00009379192,0.00001020193,0.02384847,0.0006168192,0.00004765976,0.00002284225,0.0003807327,0.0003408461,0.0001669535,0.0005585786,0.9738414,0.00007168872],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006471205,0.00006823797,0.00003203592,0.0001356932,0.00003307785,0.00001845604,0.9978042,0.00007595251,0.001767684],"genre_scores_gemma":[0.001379647,0.0004736504,0.0006206835,0.0001915775,0.00002360808,0.0001358305,0.987703,0.0001803902,0.009291777],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1075011,"threshold_uncertainty_score":0.4295464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02097570430834593,"score_gpt":0.2460840329449809,"score_spread":0.225108328636635,"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."}}