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Record W2030966685 · doi:10.1177/0142331207080153

Real-time process monitoring of micromoulding using integrated ultrasonic sensors

2007· article· en· W2030966685 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

VenueTransactions of the Institute of Measurement and Control · 2007
Typearticle
Languageen
FieldEngineering
TopicUltrasonics and Acoustic Wave Propagation
Canadian institutionsMcGill UniversityCarleton UniversityNational Research Council Canada
FundersEngineering and Physical Sciences Research CouncilNational Research Council Canada
KeywordsUltrasonic sensorMaterials scienceExtrusionBarrel (horology)Process (computing)ShrinkageAcousticsUltrasonic testingInsert (composites)Composite materialMechanical engineeringComputer scienceEngineering

Abstract

fetched live from OpenAlex

Real-time, non-intrusive and non-destructive process monitoring of micromoulding has been performed using novel ultrasonic sensors integrated onto the barrel and mould insert with an ultrasonic pulse-echo technique. The relative variation of the polymer melt temperature inside the extrusion barrel can be obtained using the ultrasonic velocities of the melt measured at the barrel during extrusion. Melt flow arrival in the mould, and solidification, shrinkage and detachment of the polymer inside the mould cavity are also successfully monitored. The presented ultrasonic sensors and technique enable optimizing the micromoulding process, and improving quality of the moulded parts and process efficiency.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.154
Threshold uncertainty score0.341

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 head0.017
GPT teacher head0.222
Teacher spread0.206 · 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