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Record W2145624828 · doi:10.1109/icsmc.1995.537891

Knowledge systematization in the international IMS research program

2002· article· en· W2145624828 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
FieldEngineering
TopicFlexible and Reconfigurable Manufacturing Systems
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaIndustry Canada
KeywordsFrontierComputer scienceResearch programEngineering managementTest (biology)Knowledge managementScale (ratio)Systems engineeringProcess managementEngineering

Abstract

fetched live from OpenAlex

The international intelligent manufacturing systems (IMS) research program is an attempt to systematize and make operational world-wide knowledge of advanced manufacturing systems as a basis for new paradigms. This paper gives an overview of the IMS objectives, the six test cases to date, and the proposed future research activities. It describes the coordination of the IMS GNOSIS test case, concerned with knowledge systematization to support the full manufacturing life cycle. The systematic acceleration of scientific research was a major objective of the proposed Japanese human frontier research program. IMS is one of the first attempts to achieve such acceleration on a large-scale, and the paper concludes with a discussion of the need for system-theoretic models for the complex socio-technical systems involved in international collaborative research.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.936
Threshold uncertainty score0.828

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.001

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 head0.106
GPT teacher head0.327
Teacher spread0.220 · 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