OPTIMIZATION BUILDING ENCLOSURE REDESIGN TO FULFILL NATURAL LIGHTING INTENSITY STANDARD AND OTTV IN SOUTH QUARTER JAKARTA OFFICE BUILDING BASED ON GREENSHIP CRITERIA
Bibliographic record
Abstract
Abstract- South Quarter is one of the buildings that applies green building principles located in South Jakarta. Based on the Greenship assessment standards, energy saving efforts to decrease OTTV value on some office floors are considered optimal (≤33.25W/m2), but haven’t occupied the natural lighting intensity standard (≤30%). Based on the existing design, there are things which can be optimized such as the color selection of floor, ceiling, and envelope material. The lighting optimization will certainly affect the heat that goes into the building, therefore the effort of optimizing South Quarter office façade design for the fulfillment of natural lighting intensity and OTTV value based on the Greenship criteria is important to do.This research uses descriptive-evaluative research with quantitative-qualitative approach. The evaluative research is done by controlling the building envelope design (simulation method), then observing the effects. These effects are devoted to 2 points, which are natural lighting intensity and OTTV value. The qualitative approach is done by observing the object of study.By replacing glass material, floor material, adding shading elements and light shelf, the optimization of building envelope design has increased the natural lighting intensity by 14.84-30.71% to occupy the Greenship criteria, while maintaining the OTTV standard. Key Words: natural lighting intensity, OTTV value, Greenship, material, shading, light shelf.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".