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Record W2247921322 · doi:10.2172/1089084

Predictive Engineering Tools for Injection-Molded Long-Carbon-Fiber Thermoplastic Composites

2013· report· en· W2247921322 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

Venuenot available
Typereport
Languageen
FieldEngineering
TopicInjection Molding Process and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsCorporationQuarter (Canadian coin)EngineeringEngineering managementBusinessManufacturing engineeringPolitical scienceLawHistory

Abstract

fetched live from OpenAlex

This quarterly report summarizes the status for the project planning to complete all the legal and contract documents required for establishing the subcontracts needed and a Cooperative Research and Development Agreement (CRADA) with Autodesk, Inc., Toyota Motor Engineering and Manufacturing North America (Toyota), and Magna Exterior and Interiors Corporation (Magna). During the second quarter (1/1/2013 to 3/31/2013), all the technical and legal documents for the subcontracts to Purdue University, University of Illinois, and PlastiComp, Inc. were completed. The revised CRADA documents were sent to DOE, Autodesk, Toyota, and Magna for technical and legal reviews. PNNL Legal Services contacted project partners’ Legal counterparts for completing legal documents for the project. A non-disclosure agreement was revised and sent to all the parties for reviews.

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 categoriesMeta-epidemiology (narrow)
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 score0.849
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.226
Teacher spread0.201 · 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

Quick stats

Citations9
Published2013
Admission routes1
Has abstractyes

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