MétaCan
Menu
Back to cohort
Record W6995185911

UKERNA SLA 2005-6

2005· other· en· W6995185911 on OpenAlexfundno aff

Bibliographic record

VenueJISC Information Environment Repository (Jisc) · 2005
Typeother
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsnot available
FundersQueen's UniversityUniversity of BirminghamUniversity of BristolCardiff UniversityUniversity of GlasgowUniversity of ReadingUniversity of NottinghamUniversity of LeedsUniversity of OxfordUniversity of GreenwichUniversity of Dundee
KeywordsMean time between failuresService (business)Failure rateRemainderDuration (music)
DOInot available

Abstract

fetched live from OpenAlex

The definitions of terms in this clause apply to the individual service levels defined in the remainder of this annex.2. Despite the name, the mean time between failures is manipulated for the purposes of aggregation and averaging as a failure rate, in incidents per hour.Thus a target MTBF for the Basic Transmission Service of more than a thousand hours is a rate of less than 0.001 incidents per hour, and is calculated each month by dividing the number of failures by the number of institutions and the number of hours in the month (e.g.720).The MTBF figure for a twelve-month period is produced by averaging the rates observed in each of the constituent months of the period. A1.6 Loss of InformationSeveral services operated by UKERNA accept data submitted by client institutions and then make it available to the same and to other client institutions.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.309
Threshold uncertainty score0.986

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0020.001
Scholarly communication0.0050.004
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.3090.310

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 head0.005
GPT teacher head0.221
Teacher spread0.216 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueJISC Information Environment Repository (Jisc)Same topicEpilepsy research and treatmentFrench-language works237,207