{"id":"W6958025225","doi":"10.6068/dp14ba817f68610","title":"Trend 1960 - 2008. Statistics Canada. CANSIM: Manufacturing - Food, Beverage and Tobacco | Country: Canada | Table: Supply and disposition of food in Canada | Variable: Concentrated skim milk, Total disposition | Units: (kilolitres), 1960-2008. 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; Food supply; Descriptive statistics; Census; Summary statistics; Statistical analysis; Statistics education; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001920941,0.002274474,0.002522522,0.008663384,0.003105776,0.00447194,0.004822068,0.001465582,0.0865292],"category_scores_gemma":[0.0167268,0.001747449,0.002038126,0.04088403,0.0006909687,0.002549183,0.002208718,0.003160545,0.05467225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05355693,"about_ca_system_score_gemma":0.139981,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9945512,"about_ca_topic_score_gemma":0.9920502,"domain_scores_codex":[0.995931,0.0002334582,0.0004193309,0.0005028423,0.001958181,0.0009551489],"domain_scores_gemma":[0.9678816,0.001032716,0.001003702,0.0008573494,0.02782184,0.001402945],"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":[0.00002002617,0.000005661249,0.0009468052,0.0002405439,0.00001807181,0.00000663816,0.00002098098,0.00009968942,0.000009145115,0.0003983565,0.9968088,0.001425152],"study_design_scores_gemma":[0.0001190955,0.00001083268,0.02180285,0.000700267,0.000057618,0.00002459838,0.0003964949,0.0003292348,0.0001554944,0.0005423445,0.9757916,0.00006952908],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004939816,0.00005135895,0.00002352127,0.0001212969,0.00002926962,0.00001373032,0.9987321,0.00005216207,0.0009269782],"genre_scores_gemma":[0.0009557753,0.0003507251,0.000413255,0.0001708277,0.00002147496,0.0001223878,0.992767,0.0001127685,0.005085735],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9134708,"threshold_uncertainty_score":0.3885846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01276444205847138,"score_gpt":0.2117351654857457,"score_spread":0.1989707234272743,"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."}}