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Record W2468136605

KEBUTUHAN FREKUENSI PENERBANGAN RUTE JAKARTA – JOGYAKARTA – JAKARTA PT INDONESIA AIR ASIA

2016· article· id· W2468136605 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typearticle
Languageid
FieldEngineering
TopicUrban Transport Systems Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Field surveyGeographyAdvertisingBusinessCartography
DOInot available

Abstract

fetched live from OpenAlex

PT. Indonesia Air Asia is one of the Indonesia national flight company which is using Airbus 320-200 and Boeing 737 – 300 for route Jakarta – Yogyakarta – Jakarta. The problem of the research is the high frequency of the flight based on the number of passengers on that route. Using two methods; field and library research and analyzed by market share analysis, linear trend, seat load factor (SFL), to find out the needs of flight frequency, the number of passengers, and diagram rotation. The result shows that there is an addition to the number of passengers and flight frequency of the route. Based on the analysis, Y = a+bX, the fluctuation trend pax on the first quarter route Jakarta – Yogyakarta is 68 % and on the second quarter route Yogyakarta – Jakarta is 67 %. For SFL, route Jakarta – Yogyakarta in the third quarter is 86 % dan the opposite route is 80 %.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.209
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.010

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 head0.008
GPT teacher head0.186
Teacher spread0.178 · 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

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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