Operating performance of passive infrared counters under different seasons
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
This research analyzes the operating performance of two commercially available passive infrared counters (PICs) of pedestrians as a function of site, summer, fall and winter seasons in terms of counter sensitivity. Three sites were selected for field analysis in Winnipeg, Canada. Based on a sample of 24,690 people counted by the two PICs from July 2014 to February 2015, this research found that with a 95 percent confidence, Eco-Counter’s sensitivity ranged from 73 to 97 percent while TRAFCO’s ranged from 57 to 97 percent related to people occlusion. On weekdays, Eco-Counter’s absolute error was 16 percent and TRAFCO’s was 18 percent. On weekends, Eco-Counter’s absolute error was 18 percent and TRAFCO’s was 21 percent. In addition to people occlusion, site, seasons, and time of week (weekday and weekend) were found to affect the operating performance of the PICs. Correction factors were also calculated per counter, site, and seasons.
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