{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008835728,0.0001728771,0.0002229387,0.0000203709,0.001063189,0.0001174062,0.0001280303,0.0001242122,0.0002079948],"category_scores_gemma":[0.00002552467,0.0001004883,0.0001009056,0.0001796628,0.001061879,0.0003272003,0.00007254848,0.0000765365,0.000009636142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000341557,"about_ca_system_score_gemma":0.00002935532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009255963,"about_ca_topic_score_gemma":0.009158478,"domain_scores_codex":[0.9988529,0.00005379011,0.0002397283,0.0002111104,0.0003197594,0.0003226814],"domain_scores_gemma":[0.9993806,0.00005664549,0.0001100455,0.0001192889,0.0002041105,0.0001292677],"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":[0.00004410262,0.0001439774,0.02942253,0.00003961751,0.0001729409,0.000006328202,0.01623565,0.000001711632,0.00006485197,0.03498025,0.9183714,0.0005166388],"study_design_scores_gemma":[0.0002458689,0.0002791459,0.2917168,0.00003185244,0.00004846882,0.000008257655,0.02534693,0.000001643669,0.0001657171,0.000803032,0.6811358,0.0002165191],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8741931,0.0008832547,0.00001029481,0.002856554,0.0005604713,0.0003559131,0.0001672018,0.00007238471,0.1209009],"genre_scores_gemma":[0.9953908,0.000319978,0.0002123681,0.0001061464,0.0008703875,0.00003431462,0.00009645509,0.000005724272,0.002963836],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2622942,"threshold_uncertainty_score":0.8177297,"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."}}