{"id":"W2911141289","doi":"","title":"The North American Transborder Freight Database - TransShipment","year":2017,"lang":"en","type":"dataset","venue":"","topic":"Law, logistics, and international trade","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transshipment (information security); Truck; Commodity; Database; Business; Pipeline (software); Transport engineering; International trade; Engineering; Operations research; Computer science; Finance","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":[0.0007749684,0.002139743,0.001281359,0.004877287,0.0009903904,0.001916974,0.002516584,0.001682288,0.03071547],"category_scores_gemma":[0.003270222,0.0006038219,0.0010791,0.009923354,0.0004357236,0.001324265,0.001606061,0.001859403,0.05109561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001478652,"about_ca_system_score_gemma":0.004005247,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07987273,"about_ca_topic_score_gemma":0.1051043,"domain_scores_codex":[0.9989082,0.0001355819,0.0001183722,0.0002825462,0.0003564076,0.0001989523],"domain_scores_gemma":[0.9977532,0.0002839456,0.0002745346,0.0004275975,0.0009426714,0.0003180501],"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":[0.00004891224,0.00003937115,0.001356336,0.0001160106,0.00002329338,0.00002291561,0.00001786163,0.0002838637,0.00005404934,0.0003127248,0.9957935,0.001931141],"study_design_scores_gemma":[0.0002210465,0.00002800755,0.01862022,0.0002230415,0.00005125088,0.00009429834,0.0002271926,0.001813262,0.0004271166,0.0009870142,0.9772486,0.00005900398],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006722793,0.00005381569,0.00005320987,0.00005818585,0.00002788465,0.00001136099,0.9983982,0.0001737482,0.0005512753],"genre_scores_gemma":[0.0004972572,0.00003606317,0.00009844649,0.00002037101,0.000006404816,0.00004058943,0.9987149,0.00002449751,0.0005614613],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9201273,"threshold_uncertainty_score":0.1588156,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03496545326104623,"score_gpt":0.2742169884802331,"score_spread":0.2392515352191869,"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."}}