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.
Bibliographic record
Abstract
Currently, the number of a shopping center building is increasing because most people want to go a shopping center building easily for buying many things and eating some foods. That are a normal trend these days. However, the increasing number of shopping center buildings has been increasing the number of shopping center building fires which also have been making social problems. Therefore, this study was conducted for the fire department connection among other fire facilities because it is important for fire suppression. The research subject is on the fire department connections that are on 70 shopping center buildings of more than 5 years old constructed. Survey and analysis were conducted for 70 fire department connections. The result of this study is that all installed fire department connections have a type that includes one or two holes each at 65mm wide, and the average distance between fire department connections and access roads is 4.85m. The total average percentage of insufficiency conditions such as drive ways for fire trucks, visibility, accessibility, pressure range sign, installed height, cover of the hole, etc. is 45.3%. So improvement of law and systems, that are fire facility construction and maintenance implementations, will be needed in my opinion.
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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 it