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Record W2022468748 · doi:10.1177/1063293x06065538

Customer-driven Collaborative Product Assembler for Internet-based Commerce

2006· article· en· W2022468748 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

VenueConcurrent Engineering · 2006
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsnot available
FundersNational Research Council CanadaHong Kong Polytechnic University
KeywordsThe InternetComputer scienceProduct (mathematics)Process (computing)Web applicationProcess managementSoftware engineeringWorld Wide WebEngineeringOperating system

Abstract

fetched live from OpenAlex

In this study, a real-time collaborative 3D assembling system (Co-assembler) has been described that allows casual customers to interactively and virtually configure the 3D products over the Internet. It provides a framework for a web-based 3D assembly system that uses a customizable product model to significantly simplify the configuration and the assembly process, and a customer-driven recommendation helper to assist the customers make their design decisions. Two assembly-specific data formats - Assembly ML and Parametric Product ML are developed for archival and data transfer. The system aims to capture the customers’ needs and convert them into technical specifications, indirectly helping to promote e-commerce for manufacturing enterprises.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.978
Threshold uncertainty score0.908

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 head0.010
GPT teacher head0.222
Teacher spread0.212 · 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