{"id":"W6939244084","doi":"10.6068/dp1696d581aad5","title":"TREND: Bureau of Transportation Statistics. Border Crossings: Border Crossings - All Vehicles, 01/1996 - 12/2016. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 007-003-001Bureau of Transportation Statistics. Border Crossings: Border Crossings - All Incoming People, 01/1996 - 12/2016. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 007-003-002Bureau of Transportation Statistics. Border Crossings: Border Crossings - Loaded Containers, 01/1996 - 12/2016. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 007-003-003Bureau of Transportation Statistics. Border Crossings: Border Crossings - Empty Containers, 01/1996 - 12/2016. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 007-003-004Bureau of Transportation Statistics. Border Crossings: Border Crossings - Trucks, 01/1996 - 12/2016. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 007-003-005Bureau of Transportation Statistics. Border Crossings: Border Crossings - Trains, 01/1996 - 12/2016. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 007-003-006Bureau of Transportation Statistics. Border Crossings: Border Crossings-Loaded Truck Containers, 01/1996 - 12/2016. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 007-003-007Bureau of Transportation Statistics. Border Crossings: Border Crossings - Empty Truck Containers, 01/1996 - 12/2016. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 007-003-008Bureau of Transportation Statistics. Border Crossings: Border Crossings - Loaded Rail Containers, 01/1996 - 12/2016. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 007-003-009Bureau of Transportation Statistics. Border Crossings: Border Crossings - Empty Rail Containers, 01/1996 - 12/2016. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 007-003-010Bureau of Transportation Statistics. Border Crossings: Border Crossings - Personal Vehicles, 01/1996 - 12/2016. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 007-003-011","year":2019,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Closing (real estate); Agency (philosophy); Statistical analysis; Land use; Unit (ring theory); Resource (disambiguation); Transportation infrastructure; Port (circuit 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002538804,0.002416335,0.001853152,0.007743229,0.001727348,0.005507453,0.003665572,0.001766926,0.3003091],"category_scores_gemma":[0.03387778,0.001468609,0.001585718,0.02752519,0.0005089634,0.006746293,0.002702139,0.003418773,0.357269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004070594,"about_ca_system_score_gemma":0.009123861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1329461,"about_ca_topic_score_gemma":0.1040007,"domain_scores_codex":[0.9960092,0.000564093,0.0007094947,0.0007839091,0.001525691,0.0004074606],"domain_scores_gemma":[0.9766091,0.00270691,0.001763333,0.001886749,0.01600434,0.001029641],"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":[0.00001464695,0.000006141122,0.0004440787,0.0001382986,0.000005454728,0.000004150197,0.00001568735,0.00004174891,0.000006359805,0.000335019,0.9972728,0.001715666],"study_design_scores_gemma":[0.00006407573,0.00001033857,0.00365763,0.0006571013,0.00001912332,0.00001654609,0.0003772917,0.0001474413,0.00008543696,0.001119,0.9938168,0.00002928385],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000671579,0.00006978524,0.0001051681,0.0003144497,0.0002299798,0.00004046038,0.9931508,0.000229655,0.00579256],"genre_scores_gemma":[0.000610676,0.0003481964,0.0004674167,0.0002520663,0.0001036367,0.000340942,0.9875063,0.0004197307,0.009950989],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3003091,"threshold_uncertainty_score":0.9980242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02697341705260332,"score_gpt":0.306426861388067,"score_spread":0.2794534443354637,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). 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