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Record W1927166915 · doi:10.1109/mcom.2015.7295464

Future railway communications [Guest Editorial]

2015· article· en· W1927166915 on OpenAlexaff
David W. Matolak, Marion Berbineau, David G. Michelson, Chen Chen

Bibliographic record

VenueIEEE Communications Magazine · 2015
Typearticle
Languageen
FieldEngineering
TopicSatellite Communication Systems
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsScope (computer science)TelecommunicationsIntelligent transportation systemAutomotive industryComputer scienceVehicular communication systemsCommunications satelliteCommunications systemAutomotive electronicsTelecommunications equipmentVehicular ad hoc networkSatelliteTransport engineeringEngineeringWirelessWireless ad hoc network

Abstract

fetched live from OpenAlex

The growth of intelligent transportation systems (ITS) has recently accelerated as governments and regulators seek to use ITS to achieve important economic and policy goals. ITS must be efficient, environmentally friendly ("green"), and, of course, safe. The scope of ITS is broad, and all transportation modes will require communications, including future vehicular (automotive) systems and vehicle-to-vehicle/vehicle-to-infrastructure (V2V/V2I) communications, aeronautical communications, maritime communications, satellite communications, railway communications, and possibly others.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.818
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0060.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.003

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 head0.059
GPT teacher head0.294
Teacher spread0.235 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations2
Published2015
Admission routes1
Has abstractyes

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