ADAPTASI SEKUEN FILM HOROR PADA ARSITEKTUR SEBAGAI UPAYA MEMUNCULKAN KONDISI HOROR
Bibliographic record
Abstract
Kondisi horor bersifat universal dan abadi, dapat dialami oleh setiap manusia yang mengamatinya. Fenomena tersebut dapat diamati secara berulang kali dalam waktu yang berbeda-beda, sehingga dapat dilabel sebagai sebuah tipologi. Comparative case-study analysis dilakukan pada media horor untuk mengidentifikasi ciri dan pola yang membangun kondisi horor. Dengan begitu, tipologi horor yang telah teridentifikasi nantinya dapat diterapkan pada desain untuk memunculkan kondisi horor yang serupa dengan yang diamati pada media horor. Film ditentukan sebagai media yang dapat diandalkan sebagai preseden karena kemudahan menganalisis sekuen dan vista yang ditayangkan. Hasil penelitian berupa parameter yang membangun kondisi horor, identifikasi proses translasi kondisi horor pada arsitektur, dan wujud arsitektur horor yang dapat diimplementasikan dalam perancangan.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.007 |
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; both teacher heads agree on what is shown here.
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".