{"id":"W6919968263","doi":"10.6068/dp14ba7c10a2c1","title":"Trend 2001 - 2004. Statistics Canada. CANSIM: Science and Technology - Research and Development | Country: Canada | Table: Federal expenditures on science and technology, by major departments and agencies | Variable: Agriculture and Agri-Food Canada (x 1,000,000), Extramural, Related scientific activities | Units: $CAD, 2001-2004. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-182.","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; Census; Publication; Official statistics; Statistical analysis; Statistics education; Socioeconomic status; Publishing; 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":[0.002389875,0.002843982,0.003220537,0.01126897,0.003856463,0.006533949,0.005319018,0.001849717,0.1089378],"category_scores_gemma":[0.02201128,0.002192942,0.002226251,0.05307723,0.0007725739,0.003308106,0.002495793,0.003681296,0.06875685],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07157149,"about_ca_system_score_gemma":0.1874431,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9944899,"about_ca_topic_score_gemma":0.9913006,"domain_scores_codex":[0.9940035,0.0003410387,0.0006280551,0.0006469444,0.003036458,0.001344157],"domain_scores_gemma":[0.9519523,0.001675505,0.001326696,0.001225778,0.04175038,0.002069331],"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":[0.00001928616,0.000005583738,0.000613753,0.0002113368,0.00001504405,0.000005537084,0.000014126,0.0001027001,0.000007098523,0.0003988416,0.9972453,0.001361352],"study_design_scores_gemma":[0.0001213832,0.000009838787,0.01423039,0.0006727212,0.00005584167,0.00002038164,0.0003493315,0.0003944309,0.0001710129,0.0006345381,0.9832641,0.00007594583],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004163865,0.00005974475,0.00002501842,0.0001661098,0.00004013962,0.00001650555,0.9982044,0.00007548578,0.001370985],"genre_scores_gemma":[0.0008030236,0.0004381919,0.0004754174,0.0002028365,0.00002390475,0.0001519136,0.9908425,0.0001672797,0.006895035],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9284285,"threshold_uncertainty_score":0.51929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03393893204133902,"score_gpt":0.2693006337448139,"score_spread":0.2353617017034749,"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."}}