{"id":"W6901684196","doi":"10.6068/dp15ad7c8b05290","title":"TREND: United States Census Bureau. US Trade by Commodity Group: Exports by State | State: Maryland | WCO Harmonized Trade Num: 00 | Consumer Item: All Trade, 01/2002 - 11/2016. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 001-035-002","year":2017,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Liberian dollar; Commodity; State (computer science); Population; Value (mathematics); Documentation","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":[0.001083935,0.001829702,0.001500223,0.006037295,0.0008859323,0.002539638,0.002416535,0.001059667,0.09824159],"category_scores_gemma":[0.01042321,0.000968756,0.001115198,0.02132952,0.0003482872,0.003156252,0.001614323,0.002698443,0.1202535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002275889,"about_ca_system_score_gemma":0.005494931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1196534,"about_ca_topic_score_gemma":0.0838226,"domain_scores_codex":[0.998264,0.0002023073,0.0002925527,0.000434584,0.0005868252,0.000219818],"domain_scores_gemma":[0.9922476,0.0007239664,0.0008458897,0.0006504472,0.00518956,0.0003426338],"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":[0.00001288106,0.000007970356,0.0006994202,0.0001975893,0.00001241473,0.000005257569,0.00001545399,0.00006500709,0.00001551704,0.0003755511,0.9969578,0.001635286],"study_design_scores_gemma":[0.00007530295,0.00001032647,0.008862768,0.0004337363,0.00003065283,0.00002584947,0.0001883773,0.0001796569,0.00009570981,0.0007839481,0.9892877,0.00002603547],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006054533,0.00003362699,0.00004935645,0.0000662706,0.00003397024,0.00001741126,0.9985715,0.0000706318,0.001096603],"genre_scores_gemma":[0.0004929233,0.0001526476,0.0002868346,0.0000987592,0.00002726755,0.0002035002,0.996991,0.0001018471,0.001645212],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1196534,"threshold_uncertainty_score":0.3286509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04073475059286176,"score_gpt":0.2872869922234473,"score_spread":0.2465522416305856,"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."}}