{"id":"W6957498136","doi":"10.6068/dp174cd7aab8880","title":"TREND: United States Census Bureau. International Trade Datasets: Imports by Advanced Technology Products Code | Indicator: Air Charges, 2013 - 2019. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 001-067-007","year":2020,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Commodity; Product (mathematics); Publishing; Principal (computer security); Resource (disambiguation); Code (set theory)","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":[0.00127541,0.001654279,0.001350188,0.006420196,0.0007881525,0.002529074,0.002277556,0.001167098,0.0902992],"category_scores_gemma":[0.01268743,0.0009578938,0.001297736,0.02277444,0.0003436881,0.002852441,0.001654955,0.002717989,0.08699387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00237114,"about_ca_system_score_gemma":0.00567178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1089615,"about_ca_topic_score_gemma":0.0821473,"domain_scores_codex":[0.9982481,0.0001924848,0.0003472958,0.0003597764,0.0006140969,0.0002383897],"domain_scores_gemma":[0.990795,0.0009548935,0.00101094,0.0006920462,0.006181316,0.0003659399],"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":[0.00001609016,0.0000086604,0.0007719984,0.0002528441,0.00001379095,0.000006173451,0.00001551831,0.00007362787,0.0000163129,0.0004522139,0.9969189,0.001453771],"study_design_scores_gemma":[0.0001220046,0.00001322497,0.01141801,0.0006498188,0.00004358103,0.00002899501,0.0002233197,0.0002580669,0.0001310553,0.001109689,0.9859643,0.00003784931],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006400678,0.00003414701,0.00004733502,0.00006739099,0.00003400775,0.00001663873,0.9988347,0.00006397766,0.0008378146],"genre_scores_gemma":[0.0005185084,0.0001513265,0.0002851966,0.00009812052,0.00002814502,0.0001971545,0.9971136,0.00009221721,0.001515795],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1089615,"threshold_uncertainty_score":0.3020809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02343331255890257,"score_gpt":0.2827331662628469,"score_spread":0.2592998537039444,"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."}}