{"id":"W6939144140","doi":"10.6068/dp15e770b7d8f72","title":"Trend 1961 - 2011. Food and Agriculture Organization of the United Nations. Food and Agriculture Organization Statistics: Food Supply - Livestock, Fish | Country: Canada | Item: Animal Products | Element: Protein supply quantity (g/capita/day) - g/capita/day, 1961-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 067-001-003.","year":2017,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Livestock; Per capita; Food systems; Food supply; Population; Food processing; Food security","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":[0.001561966,0.001707641,0.001650799,0.004778934,0.000779519,0.002310458,0.00258062,0.001096634,0.06596019],"category_scores_gemma":[0.01139813,0.0009926226,0.001130789,0.02138192,0.000314446,0.002195906,0.001393589,0.00235182,0.06444031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004333444,"about_ca_system_score_gemma":0.007906009,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3189816,"about_ca_topic_score_gemma":0.2480713,"domain_scores_codex":[0.9982974,0.0001901576,0.0002592811,0.0003514259,0.000637961,0.0002637857],"domain_scores_gemma":[0.9915463,0.0009844498,0.0009472355,0.0006370164,0.005499514,0.0003853941],"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":[0.00003316381,0.00001153809,0.001416296,0.0003891457,0.00002336728,0.000007892226,0.00001388658,0.0001360506,0.00002615946,0.0003394997,0.9959186,0.00168443],"study_design_scores_gemma":[0.0001269852,0.00001683353,0.02290211,0.0006290243,0.00004058783,0.00002543129,0.0001943814,0.0002154727,0.0001657792,0.0005601802,0.9750837,0.00003948484],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005239392,0.00002602334,0.00001977585,0.00003713412,0.000019811,0.000007558,0.9993937,0.00002305243,0.0004206021],"genre_scores_gemma":[0.0003026769,0.00007948041,0.0001483473,0.00003200912,0.000009492644,0.00008402076,0.9983978,0.00002664704,0.0009196051],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6810185,"threshold_uncertainty_score":0.6342497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01501123732670181,"score_gpt":0.2178801788814385,"score_spread":0.2028689415547367,"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."}}