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Record W6977004931 · doi:10.6068/dp14baeeb59e941

Trend 1988 - 2014. Bureau of Transportation Statistics. Arrivals (Airline Performance): Arrivals - 15 Minute or more delay | Country: USA | State: Virgin Islands, 1988-2014. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 007-001-004.

2015· other· en· W6977004931 on OpenAlexaboutno aff

Bibliographic record

VenueData Planet · 2015
Typeother
Languageen
FieldSocial Sciences
TopicEducation Methods and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsNonStopAviationGround transportationCONQUESTArrival timeAir traffic controlTransit (satellite)Quarter (Canadian coin)Statistical analysis

Abstract

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Bureau of Transportation Statistics (2015). Arrivals (Airline Performance): Arrivals - 15 Minute or more delay | Country: USA | State: Virgin Islands, 1988-2014. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. [Data-file]. Dataset-ID: 007-001-004. Dataset: A flight arriving 15 minutes or more after the scheduled time. Airline on-time data are reported each month to the United States Department of Transportation (DOT), Bureau of Transportation Statistics (BTS) by US air carriers that have at least 1 percent of total domestic scheduled-service passenger revenues, plus additional carriers that report voluntarily. The data cover nonstop scheduled-service flights between points within the US as described in 14 CFR Part 234 of DOT's regulations. This dataset contains on-time arrival performance data. Gate arrival time is the instance when the pilot sets the aircraft parking brake after arriving at the airport gate or passenger unloading area. Data are reported for the nation, by state, and by airport and airline. Airline mergers result in various reporting changes over the period. Joint reporting begins after Federal Aviation Administration approval of a single operating certificate. (1) January 2006: US Airways (US) and America West (HP) start to report jointly as US Airways (US). (2) January 2010: Delta (DL) and Northwest (NW) start to report jointly as Delta (DL). (3) January 2012: United (UA) and Continental (CO) start to report jointly as United (UA). (4) January 2012: Atlantic Southeast (EV) and ExpressJet (XE) start to report jointly as ExpressJet (EV), presented here as ExpressJet Combined (E*). For data through December 31, 2011, use the code EV for Atlantic Southeast and the code XE for ExpressJet. Beginning with January 1, 2012 data, use the code E* for ExpressJet Combined. Category: Transportation and Traffic, Industry, Business, and Commerce Source: Bureau of Transportation Statistics The Bureau of Transportation Statistics (BTS) was established as a statistical agency in 1992. The Intermodal Surface Transportation Efficiency Act (ISTEA) of 1991 created BTS to administer data collection, analysis, and reporting and to ensure the most cost-effective use of transportation-monitoring resources. BTS brings a greater degree of coordination, comparability, and quality standards to transportation data, and facilitates in the closing of important data gaps. http://www.bts.gov/ Subject: Air Transportation, Airline Industry, Business Travel, LeisureTravel, Airlines, Airline Operations, Passenger AirTransportation, Airports, Flight Arrivals

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.261
Threshold uncertainty score0.520

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.015
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0670.079

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.073
GPT teacher head0.372
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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