A Soft Metric for Assessing the Compliance of WLAN Devices
Bibliographic record
Abstract
The goal of this paper is to derive a soft metric for assessing the compliance of the medium access mechanism of commercially available Wi-FiTMcertified units with the IEEE 802.11 standard. The metric is used in conjunction with data collected through a practical testbed based on a Universal Software Radio Peripheral (USRP). The metric derived in this paper captures three compliance aspects: 1- the statistical distribution of the backoff random number that underlies the medium access protocol used by the WiFi Unit Under Test (UUT); 2- the accuracy of the length of the silence period between frames; and 3- the adherence to prescribed transmission opportunity limits set by the standard. The assessment of the first two aspects relies on the Kullback-Leibler distance between probability distributions, whereas the assessment of the third aspect relies on evaluating the probability with which transmission thresholds set by the standards are exceeded. The soft metric proposed in this work is in the form of a single scalar, which enables the UUTs to be ranked based on their level of compliance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".