{"id":"W6976699719","doi":"10.6068/dp14ba82b6ae871","title":"Trend 1965 - 2010. Statistics Canada. CANSIM: Manufacturing - Food, Beverage and Tobacco | Country: Canada | Table: Food available by major groups in Canada | Variable: Total creams, Food available adjusted for losses | Units: Litres per person, per year, 1965-2010. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-151.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Census; Official statistics; Summary statistics; Agriculture; Social statistics; Statistical analysis; Food processing; Food industry","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002759517,0.0008783086,0.0009899357,0.0001286468,0.0001962079,0.0004011853,0.001040952,0.0004413086,0.0142218],"category_scores_gemma":[0.00008736567,0.0009205083,4.081066e-7,0.0002136933,0.00008125098,0.0005524142,0.0002091111,0.000842875,0.00004562213],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006281054,"about_ca_system_score_gemma":0.01542408,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9999386,"about_ca_topic_score_gemma":0.9999881,"domain_scores_codex":[0.9959694,0.0001198194,0.0008368857,0.001130443,0.0009171035,0.001026373],"domain_scores_gemma":[0.9968169,0.0006363636,0.0003411224,0.001482123,0.00009819408,0.0006252563],"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":[0.00006771929,0.00003986995,0.00003139627,0.001237957,0.0004165768,0.00007307545,0.000003990318,0.000186823,0.000005418748,0.00006330802,0.9978225,0.00005137268],"study_design_scores_gemma":[0.001173466,0.0001304909,0.000004521251,0.00005906455,0.0002190346,0.0001126845,0.0005255212,0.002374787,0.000001176903,1.268664e-7,0.9943189,0.001080247],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000007713599,0.007171752,0.00002034199,0.000003760339,0.001247572,0.0006996187,0.9836119,0.0001029272,0.007134403],"genre_scores_gemma":[0.0000632813,0.0009875472,0.0002463321,0.0001941828,0.000193313,0.00005815993,0.9527184,0.0003036511,0.04523515],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03810075,"threshold_uncertainty_score":0.9993246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02352315643872086,"score_gpt":0.2111553175951517,"score_spread":0.1876321611564308,"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."}}