MétaCan
Menu
Back to cohort
Record W1524178149 · doi:10.1002/9781119941378.ch6

Model Based Availability Management: The Availability Management Framework

2012· other· en· W1524178149 on OpenAlexaff
Maria Toeroe

Bibliographic record

Venuenot available
Typeother
Languageen
FieldComputer Science
TopicSoftware System Performance and Reliability
Canadian institutionsEricsson (Canada)
Fundersnot available
KeywordsRedundancy (engineering)Computer scienceVocabularySimple (philosophy)Perspective (graphical)Logical data modelDistributed computingData scienceSoftware engineeringData modelingArtificial intelligence

Abstract

fetched live from OpenAlex

This chapter introduces the SA Forum Availability Management Framework (AMF). It looks at concepts visible through the AMF API and therefore the main concerns for application developers when integrating their design with AMF. These concepts are the component and the CSI. The AMF performs the availability management based on a model composed of logical entities that represent these two groups. It compares the main features of the different redundancy models using a simple failure scenario in a relatively simple configuration that still reflected the key points site designers would want to consider when configuring their site. The chapter looks at the information model from an administrative perspective as the model contains the status information of the AMF entities in the system and administrative operations are issued on the objects of this model representing these different entities. Controlled Vocabulary Terms redundancy

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)0.005
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.007
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0070.008
Open science0.0040.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.003

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 head0.017
GPT teacher head0.244
Teacher spread0.228 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

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
Published2012
Admission routes1
Has abstractyes

Explore more

Same topicSoftware System Performance and ReliabilityFrench-language works237,207