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Record W2497157173 · doi:10.1115/1.2005-mar-2

No Run of the Mill

2005· article· en· W2497157173 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueMechanical Engineering · 2005
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsnot available
Fundersnot available
KeywordsOrder (exchange)Las vegasBuild to orderEngineeringMillStock (firearms)Manufacturing engineeringEngineering managementManagementBusinessMechanical engineeringEconomicsProduction (economics)Finance

Abstract

fetched live from OpenAlex

This article discusses that the business of engineering has challenges of its own. Engineer-to-order (ETO) differs from make-to-stock or make-to-order businesses primarily in the amount of designing that takes place after a firm receives an order. For either of the two make-to systems, post-order engineering is insignificant. ETO firms depend heavily on engineers and designers inside the order cycle because the machine has to be imagined, then designed and detailed, before it can be built. Handling specialty is a typical ETO manufacturer. It builds lifting and turning equipment used by everyone from automakers in Toronto to stage builders in Las Vegas. Although it makes equipment mostly of a particular kind, no two orders are exactly alike. In order to make a transition from entrepreneurial, family-owned firms to professional ones, ETO companies need to make business information available to employees throughout their organizations.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score0.502

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 head0.009
GPT teacher head0.182
Teacher spread0.174 · 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