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Record W2994511161 · doi:10.35940/ijeat.f1052.0986s319

The Prospect of Turboprop Commercial Flight in Indonesia

2019· article· en· W2994511161 on OpenAlexaboutno aff
Nugraha Arifianto, Sigit S. Wibowo

Bibliographic record

VenueInternational Journal of Engineering and Advanced Technology · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicAviation Industry Analysis and Trends
Canadian institutionsnot available
Fundersnot available
KeywordsTurbopropAviationJet (fluid)AeronauticsJet fuelProfitability indexRange (aeronautics)Environmental scienceAerospace engineeringTransport engineeringEngineeringBusinessFinance

Abstract

fetched live from OpenAlex

The transportation between remote cities and different islands in Indonesia needs to be served by aviation. One possibility to connect cities with short distance is by using small aircraft, such as the turboprop aircraft. However, the feasibility of such aircraft should be examined due to its huge investment and profitability. This study tries to determine the route network of turboprop aircraft in Indonesia using Ryerson and Ge’s approach (2014) by examining spatial trends for short-haul aviation and on the regional jet routes. The possibility of turboprop flight on the regional jet routes could be assessed by a distance-based and fuel-time trade-off with three scenarios of fuel price. To validate the potential network of turboprop aircraft, binary logit model predict the probability that a route is fit served by a turboprop. This study shows that more than half of the current regional jet routes in Indonesia can be operated by turboprop aircraft. However, the route which farther than its range capability should be operated with regional jet.

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 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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.005
GPT teacher head0.203
Teacher spread0.198 · 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 designObservational
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

Citations0
Published2019
Admission routes1
Has abstractyes

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