{"id":"W6958111929","doi":"10.6068/dp15df1f4461344","title":"Trend 1996 - 2016. Bureau of Transportation Statistics. Border Crossings: Border Crossings - Train Passengers | Country: USA, 1996-2016. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 007-003-016.","year":2017,"lang":"en","type":"other","venue":"Data Planet","topic":"History of Computing Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Crew; Agency (philosophy); Statistical analysis; Closing (real estate); Work (physics); Descriptive statistics; Vehicle miles of travel; Unit (ring 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00114282,0.001056193,0.001487888,0.0003847192,0.0005760299,0.001225535,0.01018214,0.001113988,0.001674036],"category_scores_gemma":[0.0001041247,0.001022078,0.000003634881,0.0001160136,0.002174773,0.001193088,0.0006765194,0.001108897,0.0007186612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000101681,"about_ca_system_score_gemma":0.0008710489,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3645652,"about_ca_topic_score_gemma":0.0446028,"domain_scores_codex":[0.9936785,0.0002638563,0.001305791,0.002369209,0.00130446,0.001078187],"domain_scores_gemma":[0.9885935,0.0007023587,0.002203175,0.008148664,0.00004526872,0.0003070208],"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":[0.00004857972,0.0001409625,0.00001306437,0.0005564876,0.0001858641,0.0002913104,0.00005022651,0.000008129997,0.00003272273,0.002538845,0.9868264,0.00930743],"study_design_scores_gemma":[0.0008069964,0.0001721893,0.00005343989,0.0002009392,0.0002064858,0.00006410634,0.00002987765,0.004205764,4.423656e-7,0.00001331383,0.9931062,0.001140223],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[7.957599e-7,0.002778548,0.006699978,0.00002157323,0.001170949,0.0005848683,0.9820052,0.0006508736,0.006087239],"genre_scores_gemma":[0.00005080431,0.0005979519,0.0268993,0.0001083044,0.0001999547,0.00001736841,0.965357,0.0002302822,0.006539027],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3199624,"threshold_uncertainty_score":0.9998113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0368456931613295,"score_gpt":0.3232500702284852,"score_spread":0.2864043770671557,"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."}}