{"id":"W6946200687","doi":"10.25814/5c07aed43fec2","title":"Agricultural commodities: December quarter 2018","year":2018,"lang":"en","type":"article","venue":"Department of Agriculture, Fisheries and Forestry - ABARES","topic":"Legal case studies and regulations","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Quarter (Canadian coin); Agricultural productivity; Key (lock)","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":[0.0007535061,0.0004716716,0.0002198875,0.002099182,0.001081673,0.003963593,0.0005285852,0.001254053,0.1689359],"category_scores_gemma":[0.003261048,0.0002613482,0.0002286913,0.002725382,0.0003218468,0.002170806,0.0008333792,0.001531936,0.1051437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002824333,"about_ca_system_score_gemma":0.002866652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0327359,"about_ca_topic_score_gemma":0.0378617,"domain_scores_codex":[0.9989792,0.00004185075,0.00005660689,0.00008171582,0.0007237087,0.0001169896],"domain_scores_gemma":[0.9988223,0.00008032897,0.00008271576,0.00008011583,0.0008317321,0.0001028323],"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":[0.00003011597,0.00002044371,0.0002703826,0.00009260268,0.000001134511,0.00003601798,0.00006951791,0.00002619877,0.0001488011,0.004069198,0.9692415,0.0259941],"study_design_scores_gemma":[0.000002372812,0.000005295553,0.00143928,0.00004977153,4.369673e-7,0.00001243353,0.0000478482,0.00001681394,0.00007351716,0.0002585059,0.998091,0.000002532874],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.004414894,0.004914159,0.0004096495,0.007711445,0.005434247,0.0001904422,0.03923108,0.0007798097,0.9369143],"genre_scores_gemma":[0.008280313,0.004210664,0.0004321274,0.00181306,0.0006387422,0.000142416,0.01719457,0.0002911138,0.966997],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1689359,"threshold_uncertainty_score":0.5651468,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01400860805972021,"score_gpt":0.2491006634889424,"score_spread":0.2350920554292222,"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."}}