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
Abstract This paper presents the results of a survey conducted in the Canadian cities of Ottawa and Gatineau to characterize fire loads in commercial premises. The survey included various commercial establishments such as restaurants, travel agencies, and pharmacies, as well as, retail stores selling clothing, shoes, food, alcohol, computers, and computer supplies. Five different types of combustible material groups were selected as the base of analyses: textiles, plastics, wood/paper, food, and miscellaneous. The data collected were analyzed to determine the total fire load in each establishment, the fire load density, and the contribution of different combustible materials to the total fire load. A total of 168 commercial premises were surveyed with a total floor area of 17127 m 2 . The area of the surveyed stores ranged from 3.25 to 1707 m 2 . The fire load densities of the 168 surveyed stores had a lognormal distribution with a mean value of 747 MJ/m 2 , a maximum value of 5305 MJ/m 2 , a minimum value of 56 MJ/m 2 , and a standard deviation of 833 MJ/m 2 . In most stores, the 95th percentile and the mean fire load density showed a tendency to decrease with an increase of floor area, which is consistent with those of earlier surveys. Copyright © 2008 John Wiley & Sons, Ltd.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it