{"id":"W6901396302","doi":"10.6068/dp14ba805282440","title":"Trend 1960 - 1992. Statistics Canada. CANSIM: Manufacturing - Food, Beverage and Tobacco | Country: Canada | Table: Supply and disposition of food in Canada | Variable: Dry beans, Domestic disappearance | Units: Tonnes x 1,000, 1960-1992. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-151.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Official statistics; Census; Descriptive statistics; Food supply; Summary statistics; Statistical analysis; Agriculture","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":[0.0019158,0.002344755,0.002547595,0.008383192,0.003061061,0.004526098,0.00477459,0.001435644,0.08902306],"category_scores_gemma":[0.01571932,0.001748089,0.00200921,0.04220239,0.0006911643,0.002532816,0.002119984,0.003057359,0.05583279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0553259,"about_ca_system_score_gemma":0.1389989,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9951234,"about_ca_topic_score_gemma":0.9927617,"domain_scores_codex":[0.995914,0.0002307307,0.0004143622,0.0005096956,0.001973323,0.0009579378],"domain_scores_gemma":[0.9688933,0.0009632148,0.0009536345,0.0008345402,0.02693737,0.001417868],"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":[0.00002202357,0.000005965736,0.0009751861,0.0002595319,0.00001936877,0.000007150095,0.00002145789,0.0001068127,0.000009720467,0.0004194933,0.9966089,0.001544477],"study_design_scores_gemma":[0.0001275874,0.00001146143,0.02370781,0.0006856358,0.00005956852,0.00002440267,0.0004063213,0.0003377287,0.0001553365,0.0005155082,0.9738985,0.00007015388],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004938474,0.00005597209,0.00002223316,0.0001186091,0.00002877989,0.00001315497,0.9987112,0.00005199291,0.0009485913],"genre_scores_gemma":[0.001034142,0.0003810126,0.0003778068,0.0001619566,0.00002070128,0.000114678,0.9924306,0.0001110701,0.005368096],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08902306,"threshold_uncertainty_score":0.4014194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01339738312042366,"score_gpt":0.2198654424384965,"score_spread":0.2064680593180729,"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."}}