{"id":"W6958048825","doi":"10.6068/dp15ba845daad23","title":"TREND: Bureau of Transportation Statistics. Border Crossings: Border Crossings - All Vehicles | State: California, 1996 - 2016. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 007-003-001","year":2017,"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; CONQUEST; Unit (ring theory); Vehicle miles of travel; Work (physics)","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":[0.001242879,0.001501271,0.001399198,0.005303816,0.001047925,0.002904873,0.002719575,0.001036024,0.08222853],"category_scores_gemma":[0.01241216,0.001065394,0.001124172,0.01708687,0.0003308182,0.003036002,0.00140927,0.002948379,0.08482435],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003518127,"about_ca_system_score_gemma":0.007594853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2548176,"about_ca_topic_score_gemma":0.1748501,"domain_scores_codex":[0.9980853,0.0001824357,0.0002968262,0.0004375311,0.0007191615,0.0002788751],"domain_scores_gemma":[0.9887547,0.0009981946,0.001140898,0.0007778006,0.00788078,0.0004475673],"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":[0.00001474703,0.000009693717,0.001212769,0.000177767,0.00001116453,0.000004591481,0.00001356839,0.00008289733,0.000007854368,0.000313923,0.9969222,0.001228778],"study_design_scores_gemma":[0.00009983261,0.00001576958,0.01526821,0.0005998428,0.00003694581,0.00002160339,0.0003272629,0.0002621826,0.000117761,0.0007822433,0.9824316,0.00003687939],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008252622,0.00003809303,0.00003766557,0.00007847889,0.00004426879,0.00001539526,0.9985618,0.00007348817,0.00106833],"genre_scores_gemma":[0.0006364881,0.0001241629,0.0001950119,0.00005996158,0.00002666441,0.0001500209,0.997128,0.00007478119,0.001604976],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2548176,"threshold_uncertainty_score":0.5066689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.027858701906424,"score_gpt":0.3383731084259112,"score_spread":0.3105144065194873,"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."}}