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Record W6947838090 · doi:10.4224/8894882

Hardware selection recommendations for the NRC Segment Wave Generator Control System

2005· report· en· W6947838090 on OpenAlexvenueno aff

Bibliographic record

VenueNPARC · 2005
Typereport
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSingle-cell and spatial transcriptomics
Canadian institutionsnot available
Fundersnot available
KeywordsSoftwareControl systemVMEbusGenerator (circuit theory)Control (management)Selection (genetic algorithm)Digital controlHardware architecture

Abstract

fetched live from OpenAlex

In early 1991, NRC developed the second generation of its digital control system for segmented wave generators. The design used off-the-shelf technology - both hardware and software - to the extent possible at the time. The system was based on the original VME standard (VMEbus) and the pSOS real-time operating system. The system has performed well but all of the hardware has now been discontinued. The operating system software is in maintenance-only mode and the software development environment is no longer functional or supported. It has become imperative that the control system be upgraded to use current technology - both hardware and software. This report deals with the selection of new hardware for the control system. Hardware must be selected with an awareness of the options for the new operating system. The selection of the operating system will, however, be completed in a follow-on phase.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.052
Threshold uncertainty score0.173

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0520.025

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 head0.039
GPT teacher head0.269
Teacher spread0.230 · 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 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

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