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Study on flying car transportation system

2023· article· en· W4389147287 on OpenAlex
Shengxi Feng, Zeyu Huang, Junhan Wang, Jiayang Xu, Qian Zhang

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTheoretical and Natural Science · 2023
Typearticle
Languageen
FieldEngineering
TopicTransportation and Mobility Innovations
Canadian institutionsPraxis Spinal Cord Institute
Fundersnot available
KeywordsTransport engineeringGround transportationSpace (punctuation)Dimension (graph theory)Traffic congestionOrder (exchange)Development (topology)PopulationComputer scienceEngineeringBusiness

Abstract

fetched live from OpenAlex

With the rapid growth of population in large cities, traditional transportation modes like buses, private cars, and subways have formed a more serious traffic congestion or crowded situation. In order to solve this problem, engineers and researchers start to shift the research on the future development of transportation systems to the near-ground space (NGS). The flying car transportation system (FCTS) has become one of the major research projects. The concept of FCTS introduces a new dimension to transportation, utilizing unoccupied near-ground spaces to redefine the way both individuals and goods move within cities. FCTS, using flying cars as the main transportation means, has good development prospects. This article analyzes various aspects of FCTS in detail. The design of FCTS is introduced. The related technologies are summarized. The challenges of the future development of FCTS are also discussed. This article may offer a reference for the development of FCTS.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.984
Threshold uncertainty score0.169

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.252
Teacher spread0.243 · 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