Wi-Fi radiation levels at BCIT
Bibliographic record
Abstract

 Objective: To determine if there are any difference in the amount of EMF Wi-Fi radiation being emitted between three locations at the BCIT campus in Burnaby, BC. Background: Wi-Fi radiation is widely being used in today’s society for the quick access it gives us to connect to the internet. Some cities in the United Kingdom have installed many Wi-Fi devices throughout the public domain so people can be connected all the time. Furthermore, most schools are being outfitted with routers to provide internet access for their students. But, as this paper will show, new research is forcing a shift in the thinking of some policy makers in choosing to install these connections in the public domain. Method: To measure the amount of non-ionizing EMF radiation being absorbed by the body, an Extech RF meter was used. This instrument provides instantaneous and average readings for a particular area one measures. During the experiment, the RF meter was held stationary at one location for approximately 10-15 seconds in order to stabilize the reading. The average value was taken as the instantaneous reading was fluctuating. This process was done in 3 buildings at BCIT and in order to increase the reliability and validity, 30 data points were collected from each building. Results: The Tests of Assumption showed that the data was not normally distributed as there was more than one “Reject” at the 0.05 probability level. For analysis, the Krukal-Wallis One-Way ANOVA was utilized and results showed that due to a high probability level of 0.57, the H0 could not be rejected and as a result there are no differences in radiation levels being emitted into the buildings tested. Conclusion: The amount of Wi-Fi radiation in the three buildings tested at BCIT were not significantly different from one another.
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".