Turbo-Loop: a rate-adaptive digital subscriber loop (RA-DSL) for advanced ISDN access applications
Bibliographic record
Abstract
The authors report the implementation of prototype hardware and control protocols which will automatically maximize the transmission rate of individual subscriber loops. The result is a rate-adaptive digital subscriber loop (RA-DSL) technology called Turbo-Loop, which makes possible new applications such as a simple form of bandwidth-on-demand and a strategy for increased utilization of existing copper, while bridging the gap to having fiber in the loop. Results predict that Turbo-Loop can deliver 1.5 Mb/s up to 2 km, reaching subscribers to 10 km and 80 kb/s, and can provide a potential increase of 400% to 600% in the total utilization of existing copper access networks. The authors describe the hardware and software design of the RA-DSL prototype and report results of adaptive transmission rate experiments on actual copper loops. Also described are simulation studies which predict the ultimate performance of a fully developed design based on the Turbo-Loop principle.>
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".