PENERAPAN KONSEP ARSITEKTUR NARATIF TERHADAP TATA RUANG PAMERAN PADA MUSEUM
Bibliographic record
Abstract
Desain ruang pada museum sangat ditentukan oleh objek yang dipamerkan. Elemen ruang dan objek pameran saling mempengaruhi dan membentuk makna dalam suatu hubungan ruang. Permasalahan museum dewasa ini adalah ruang pameran museum sebagai salah satu elemen terpenting dalam sebuah museum kurang memperhatikan kesinambungan materi dengan tata ruang-ruang pameran museum. Tulisan ini bertujuan untuk menemukan kriteria alur serta tata ruang – ruang pamer museum yang sesuai dengan kaidah arsitektur naratif. Metode yang digunakan adalah metode komparatif melalui studi literatur dan preseden. Hasil Analisis menghasilkan dua kriteria dari masing masing aspek dalam perancangan narasi arsitektur. Pada akhirnya, arsitektur naratif menjadi pendekatan yang membantu perancang/arsitek menciptakan sinergi antara pameran dengan museum secara keseluruhan.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.101 | 0.022 |
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".