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Record W2012097631 · doi:10.1017/s1743921307011878

‘Retooling’ data centre infrastructure to support the Virtual Observatory

2006· article· en· W2012097631 on OpenAlex

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueProceedings of the International Astronomical Union · 2006
Typearticle
Languageen
FieldEngineering
TopicAstronomical Observations and Instrumentation
Canadian institutionsNational Research Council CanadaHerzberg Institute of Astrophysics
Fundersnot available
KeywordsVirtual observatoryObservatoryComputer scienceData managementSoftwareData archiveData discoveryProcess (computing)Data accessData processingData model (GIS)DatabaseWorld Wide WebOperating systemMetadataAstronomyPhysics

Abstract

fetched live from OpenAlex

The Canadian Astronomy Data Centre manages a heterogeneous collection of data from the following ground and space-based telescopes: CFHT, DRAO, FUSE , Gemini, HST , JCMT, and MOST . The archive data models implemented for these data collections are ten years old and pre-date two important developments: the Virtual Observatory and the systematic generation and management of data products. Three years ago, we began the process of supporting access to processed data products through IVOA protocols such as SIA by building a layer over the archive data models. Today, we now realise that this approach of layering VO models on archive models is not sufficient and that every archive must be re-tooled to properly support the VO – from the storage model through to the query, processing and access models. The CADC has begun an ambitious software development effort to implement a new infrastructure to serve both telescope archive and Virtual Observatory needs.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.322
Threshold uncertainty score0.346

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.011
GPT teacher head0.201
Teacher spread0.191 · 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