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Record W2080468825 · doi:10.2495/data070221

Knowledge discovery in a circle of trust

2007· article· en· W2080468825 on OpenAlex
Liam Peyton, Jun Hu

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

VenueWIT transactions on information and communication technologies · 2007
Typearticle
Languageen
FieldComputer Science
TopicPrivacy-Preserving Technologies in Data
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer scienceIdentity managementContext (archaeology)Internet privacyIdentity (music)Computer securityInformation privacyAllianceWorld Wide WebPersonally identifiable informationArchitectureAccess control

Abstract

fetched live from OpenAlex

There are now many services for individuals and businesses available over the Internet. In providing these services, personal data is exchanged. There are security and privacy concerns about protecting identity and controlling the use of personal data. The Liberty Alliance project has developed a set of standards and architecture for federated identity management. A circle of trust (CoT) is a network based on the Liberty Alliance architecture in which businesses collaborate to provide services in a manner that protects identity and carefully controls the sharing of personal data. We analyse the requirements of each stage of a knowledge discovery process in the context of a CoT, and recognize data collection as an important step with respect to protecting privacy and identity. An eHealth scenario in which data mining is used to detect prescription misuse illustrates how to implement a trusted data collection architecture in a CoT .

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.960
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0070.002
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 head0.018
GPT teacher head0.265
Teacher spread0.247 · 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