Investigation of data transmission logs using the BestFit package
Bibliographic record
Abstract
Multimedia interactive communication imposes very strict real time performance requirements on the data communication system. The design and modeling of such systems depends on the characteristics and intensity of data traffic to be carried. In this paper we look more closely on data traffic characterization and the network performance of a video conferencing system running on a packet switched LAN. Particular attention is devoted to different requirements of audio and video conferencing applications. We present an attempt at statistical modeling of data traffic intensity between two personal computers running NetMeeting application. Transmission of different scenes is analyzed, from a person reading a passage from a book to a taped recording of a rock video. For statistical testing we use the BestFit package from the Palisade Corporation, and attempt to match recorded traffic data against standard statistical distributions. The results indicate that only the video packet size can be satisfactorily modeled by standard statistical distributions, while interarrival times do not match any distributions supported by the package.
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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 | 0.000 | 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 | 0.001 | 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 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".