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Record W2154637813 · doi:10.1109/isie.2006.296063

The Grid Resource Model for Instruments and Sensors

2006· article· en· W2154637813 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsÉcole de Technologie Supérieure
FundersArgonne National LaboratoryUniversity of California, San DiegoCanarieWoods Hole Oceanographic InstitutionNational Aeronautics and Space Administration
KeywordsGridComputer scienceGrid computingMiddleware (distributed applications)e-ScienceResource (disambiguation)Semantic gridInstrument controlScientific instrumentSoftware engineeringDistributed computingSystems engineeringData scienceWorld Wide WebOperating systemEngineeringSemantic Web

Abstract

fetched live from OpenAlex

Grid applications are becoming an integral part of e-science because of science's need for intensive computing and large knowledge base. In order to have capable applications that interact with real world science, the instruments must be accessible and represented in the grid middleware. In this paper, we present the overview, design and initial implementation of a standard model for instruments and sensors inspired by the work done for IEEE1451 and built on WSRF. This model can be used by grid applications for different purposes such as laboratory planning, instrument control and sensor monitoring

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.930
Threshold uncertainty score0.231

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 science0.0000.000
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 head0.013
GPT teacher head0.221
Teacher spread0.208 · 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