A Study of Bandwidth Allocation Mechanisms . . .
Bibliographic record
Abstract
Introduction to Internet Measurement and Modeling", ACM SIGCOMM'98 Tutorial, Vancouver, Canada, September 1998, [PK95] S. Park and Y. Kim, "A Virtual Topology for WDM Multihop Lightwave Networks", in Proc. IEEE INFOCOM'95, 1995, pp. 701-708. [PRNS] R. Fromm, and D. Simpson, "A Packet Radio Network Simulator". http:// www-plateau.cs.berkeley.edu/people/davesimp/classes/wireless/ns.html [PST95] G. Parulkar, D.C. Schmidt, J.S. Turner, "IP/ATM: A Strategy for Integrating IP with ATM", ACM Computer Communication Review, 25(4): 49-58, October, 1995. [RFC1619] W. Simpson, "PPP over SONET/SDH," IFTF RFC 1619, May 1994, [RFC1661] W. Simpson, "The Point-to-Point Protocol (PPP)", IFTF RFC 1661, July 1994, [RFC1662] W. Simpson, "PPP in HDLC-like Framing," IFTF RFC 1662, July 1994. [RFC1932] R.G. Cole, D.H. Shur, C. Villamizar, "IP over ATM: A Framework Document", IFTF RFC 1932, April 1996. [RS95] R. Ramaswami and K.N. Sivarajan, "Routing and Wavelength Assignment in All-Optical Networ
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.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.006 |
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".