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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 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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.017
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0170.004

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; 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 designTheoretical or conceptual
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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