Perancangan Aplikasi Property Perumahan dengan Visualisasi Objek 3D Berbasis Mobile
Bibliographic record
Abstract
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.
How this classification was reachedexpand
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 arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | no category Domain: not available · Genre: Software About the Canadian research system: no · About a Canadian topic: no | Other design | high |
| grok | no category Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Other design | high |
| opus | no category Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Other design | medium |
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.058 | 0.023 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedLabeled directly by 3 models reading the full record.
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".