{"id":"W6976870459","doi":"10.6068/dp170c06a75543","title":"TREND: United States Census Bureau. International Trade Datasets: Exports by End-Use Code | Country: Dominican Republic, Mexico, Singapore, Thailand, United Kingdom | Indicator: Total Value | Code: 00370, 2013 - 2018. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 001-067-003","year":2020,"lang":"en","type":"other","venue":"Data Planet","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Commodity; Principal (computer security); Value (mathematics); Official statistics; Capital good; International comparisons; Capital (architecture)","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":["metaepi_narrow","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","open_science"],"category_scores_codex":[0.001939187,0.001442387,0.001321817,0.001192867,0.0004560238,0.004837958,0.01853735,0.001010103,0.002366026],"category_scores_gemma":[0.0004486038,0.001421564,0.00001589455,0.001230872,0.0008311236,0.004396117,0.01041022,0.002591664,0.0001143649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002068231,"about_ca_system_score_gemma":0.0002965702,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1544285,"about_ca_topic_score_gemma":0.01090186,"domain_scores_codex":[0.9883128,0.001035047,0.002032782,0.004410897,0.002707893,0.001500568],"domain_scores_gemma":[0.9801383,0.002296017,0.002282359,0.01389085,0.000003760857,0.001388693],"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":[0.000155721,0.0006643982,0.000009849052,0.000100926,0.000957933,0.0007982027,0.00004425265,0.0001000823,0.000003968368,0.002818188,0.9928989,0.001447572],"study_design_scores_gemma":[0.002065689,0.00008951601,0.00001884206,0.00009949774,0.0003992144,0.0004507014,0.00009394783,0.05942962,4.369546e-7,0.00001457764,0.9359477,0.001390275],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[2.377936e-7,0.000381601,0.003517546,0.003547474,0.0006668468,0.001202342,0.9891276,0.0009251809,0.000631206],"genre_scores_gemma":[0.00001101291,0.00109322,0.005849721,0.006014255,0.0005440103,0.00005824922,0.9858514,0.0004266666,0.0001514279],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1435266,"threshold_uncertainty_score":0.9998326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04838638424242692,"score_gpt":0.2974184861069481,"score_spread":0.2490321018645212,"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."}}