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Record W2767162268 · doi:10.28989/senatik.v2i0.40

KONSEP ECO-AIRPORT UNTUK MEMINIMALISASI EMISI BANDARA KULON PROGO

2016· article· id· W2767162268 on OpenAlexaff
Sitti Yani

Bibliographic record

VenueConference SENATIK STT Adisutjipto Yogyakarta · 2016
Typearticle
Languageid
FieldSocial Sciences
TopicTransportation Planning and Optimization
Canadian institutionsFraser Institute
Fundersnot available
KeywordsComponent (thermodynamics)Environmental scienceQuality (philosophy)Floor area ratioTransport engineeringCivil engineeringEngineeringBusinessEnvironmental engineering

Abstract

fetched live from OpenAlex

Eco-airport used to reinforce critical decisions and supervision, to improving the operations and quality. In simulation of Urban Modeling Interface (UMI), the environmental component is shown, FAR (Floor Area Ratio) aspects used to determine the density of buildings in an area, Lyfecycle aspect used to determine the amount of pollution produced by the building sector in the region, energy operation aspects used to know the needs of energy are in use. In this study was obtained, the content of the highest CO2 emissions in the building owned by floor 2 of ATC with 679.77 kgCO2 CO2 / m2.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.683
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.030
GPT teacher head0.290
Teacher spread0.260 · 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; both teacher heads agree on what is shown here.

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
Published2016
Admission routes1
Has abstractyes

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