Bibliographic record
Abstract
The WHOIS is a database directory of domain names and relevant contact information maintained by each top-level domain (TLD) registry, which lists all relevant registrant contact information for each domain name registration. Through its contracts, the Internet Corporation for Assigned Names and Numbers (ICANN) requires registries and registrars to collect and display technical information and contact details for all registrants. The WHOIS is an important component of the domain name system (DNS). The WHOIS is used for a wide variety of purposes by registries, registrars, registrants, law enforcement authorities, consumers, and the general public. The WHOIS may enable identification of a domain name registrant or a Web site operator who registers or uses a domain name that violates trade-mark rights, or an Internet service provider (ISP) that hosts a site with infringing materials. In addition, the WHOIS enables trade-mark owners to conduct searches to avoid possible conflicts, and helps consumers to find out who is operating commercial sites. The .ca WHOIS may be seen at http://www.cira.ca.\nIn November 2004, the Canadian Internet Registration Authority (CIRA) proposed a new policy for the .ca WHOIS. This article summarizes the current state of WHOIS issues and focuses on the CIRA proposal.
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.004 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.296 | 0.094 |
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".