MétaCan
Menu
Back to cohort
Record W1963746973 · doi:10.1109/mnet.2007.364257

The Extensive Challenges of Internet Application Measurement

2007· article· en· W1963746973 on OpenAlex
M. Arlitt, Carey Williamson

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Network · 2007
Typearticle
Languageen
FieldComputer Science
TopicInternet Traffic Analysis and Secure E-voting
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsThe InternetComputer scienceInternet Connection SharingInternet transitInternet exchange pointPoint (geometry)Reserved IP addressesTelecommunicationsInternet trafficInternet accessWorld Wide WebInternet ProtocolIP address management

Abstract

fetched live from OpenAlex

The Internet has grown dramatically and evolved significantly over the past 10 years. Although this growth provides new opportunities and many value-added services for millions of Internet users, this growth also presents ongoing challenges to networking researchers, for whom the study of the Internet itself is the raison d'etre. Other than the network link speed, there are many technical challenges that make the monitoring of Internet applications difficult. To illustrate this point, this article presents several practical examples drawn from our experiences in Internet application measurement and monitoring

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.995
Threshold uncertainty score0.240

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.029
GPT teacher head0.246
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it