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Design of Products and Processes: A Perspective from the Pyramid Model of Value System

2013· article· en· W2118643429 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAdvanced materials research · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement Theory and Practice
Canadian institutionsnot available
FundersFederation for the Humanities and Social SciencesNational Science Foundation
KeywordsValue (mathematics)Pyramid (geometry)Perspective (graphical)EngineeringField (mathematics)Resource (disambiguation)Value engineeringWork (physics)Industrial engineeringManagement scienceSystems engineeringEngineering ethicsEngineering managementManufacturing engineeringComputer scienceMechanical engineeringArtificial intelligenceOperations managementMathematics

Abstract

fetched live from OpenAlex

This paper started with the review of the evolvement of industrial engineering and illustrated the new problems encountered in modern industrial engineering. By using the Seven Elements Pyramid Model in the new generation of value engineering, researchers and practitioners are able to discover the sources and processes of value generation. Moreover, since human resource is an indispensible part of value engineering, we find it is in great need of new research methods to study workers’ physiological and psychological status in the course of work. Therefore, neuroscience methods are introduced into the modern industrial engineering, creating the new field of Neural Industrial Engineering (NeuroIE).

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score0.308

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.079
GPT teacher head0.318
Teacher spread0.240 · 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