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Record W6929026368 · doi:10.4224/21272481

1st year progress report on architecture design of distributed planning and control

2003· report· en· W6929026368 on OpenAlexaffvenue

Bibliographic record

VenueNPARC · 2003
Typereport
Languageen
Field
Topic
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsCLARITYFunction (biology)Process (computing)Control (management)ArchitectureEvent (particle physics)Systems architectureControl systemProcess control

Abstract

fetched live from OpenAlex

This report presents the progress of the NRC-NSC collaborative research project titled "Research on advanced distributed planning and control in manufacturing". Research of feature-based machining process sequencing, which is a part of supervisory planning of DPP (Task 3), is resumed first and many important results have been reached. High-level system analysis and preliminary design of the entire system have also been completed. Four of the major six tasks are further decomposed to enough details to show clearly how the whole system would function like and how the information and event flows would be. Some critical sub-functions, which would come out to be our major contributions and main efforts, are further described for the clarity of interpretation.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0030.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0360.013

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 head0.304
Teacher spread0.265 · 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
Published2003
Admission routes2
Has abstractyes

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