{"id":"W6957754430","doi":"10.6068/dp153a9d51ab581","title":"TREND: Bureau of Transportation Statistics. Border Crossings: Border Crossings - Train Passengers | State: Arizona | Port: AZ:Douglas, AZ:Lukeville, AZ:Naco, AZ:Nogales, AZ:San Luis, AZ:Sasabe, 1996 - 2014. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 007-003-016","year":2016,"lang":"en","type":"other","venue":"Data Planet","topic":"Astronomical Observations and Instrumentation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Crew; Closing (real estate); Agency (philosophy); Statistical analysis; CONQUEST; Postal service; Unit (ring theory); 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.000691195,0.001455585,0.001681748,0.0003934682,0.0003142756,0.0007064813,0.002137619,0.0008124921,0.01629749],"category_scores_gemma":[0.00003365133,0.001383488,0.00001437287,0.0001695423,0.0008460556,0.001692699,0.0002337349,0.0009450946,0.000728777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002084687,"about_ca_system_score_gemma":0.0003982571,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1303965,"about_ca_topic_score_gemma":0.03122661,"domain_scores_codex":[0.9930447,0.0002209739,0.002494795,0.001842624,0.001063469,0.001333451],"domain_scores_gemma":[0.9942634,0.0005066597,0.001282695,0.003316595,0.00003456998,0.0005960616],"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":[0.0001575053,0.0002153459,0.0001458236,0.001086666,0.000676228,0.00009589108,0.00003988014,0.0002343516,0.0001270212,0.0003515613,0.9878804,0.008989328],"study_design_scores_gemma":[0.002291164,0.0001511659,0.0004135748,0.0002065279,0.0005646939,0.00002532902,0.0001421818,0.005772368,0.000003558231,0.000005479534,0.988924,0.001499956],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002780438,0.002175669,0.004731744,0.00002026207,0.001342315,0.001200113,0.9887314,0.0003978494,0.001372824],"genre_scores_gemma":[0.0002672251,0.001811521,0.006896701,0.0001392067,0.00055466,0.00006608659,0.9880323,0.0006730012,0.001559258],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09916987,"threshold_uncertainty_score":0.9998194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01427908720031989,"score_gpt":0.2816395206174263,"score_spread":0.2673604334171064,"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."}}