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Record W2569574764 · doi:10.55601/jsm.v17i2.356

Perancangan Aplikasi Property Perumahan dengan Visualisasi Objek 3D Berbasis Mobile

2016· article· id· W2569574764 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.

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

Bibliographic record

VenueJurnal SIFO Mikroskil · 2016
Typearticle
Languageid
FieldComputer Science
TopicEdcuational Technology Systems
Canadian institutionsTellabs (Canada)
Fundersnot available
KeywordsHumanitiesProperty (philosophy)Computer scienceArt

Abstract

fetched live from OpenAlex

Property perumahan merupakan sebidang tanah yang sudah dikembangkan dan digunakan untuk kebutuhan tempat tinggal. Membuat keputusan untuk membeli sebuah property bukanlah hal yang mudah karena banyak faktor yang dapat dipertimbangkan. Biasanya seorang pembeli hanya dapat melihat property yang ingin dibeli melalui brosur, majalah, ataupun media massa lainnya, sehingga untuk melihat secara detil property yang ingin dibelinya, pembeli masih harus datang ke lokasi property tersebut. Visualisasi objek secara 3D dimaksudkan untuk mempermudah pembeli dalam melihat perumahan secara lebih realistis hanya melalui smartphone tanpa harus pergi ke lokasi perumahan tersebut.??? Visualisasi objek secara 3D akan memudahkan penjual memvisualisasikan dan memasarkan property yang akan dijual, dimana seorang agen dapat meng-upload property beserta file 3D agar dapat diakses dan juga memudahkan pembeli dalam menemukan property perumahan yang sesuai dengan yang diinginkan, dimana melalui visualisasi objek secara 3D maka pembeli seolah-olah sedang berada di lokasi property tanpa harus datang ke lokasi property tersebut.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gptno category
Domain: not available · Genre: Software
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
grokno category
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
opusno category
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Other designmedium
models agreeAgreement compares identical category sets and study designs across arms.

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)0.002
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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.843
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.004

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 head0.018
GPT teacher head0.262
Teacher spread0.244 · 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