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Record W2012422941 · doi:10.1115/imece2007-42530

Modeling and Characterization of Biomaterials Spreading Properties in Powder-Based Rapid Prototyping Techniques

2007· article· en· W2012422941 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPowder Metallurgy Techniques and Materials
Canadian institutionsUniversity of Waterloo
FundersCanadian Institutes of Health Research
KeywordsBiomaterialMaterials scienceCompactionRapid prototypingWork (physics)SlabCharacterization (materials science)Stress (linguistics)Composite materialMechanicsMechanical engineeringNanotechnologyStructural engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

In this work, the spreading properties of biomaterials, while a counter-rotating roller is used in rapid prototyping machines, are modeled and characterized. For modeling, the slab method is used in which biomaterial geometrical properties are incorporated into the model. A pressure dependent plasticity model is used as a constitutive model for biomaterial powders. In addition, the coulomb friction law for the powder-roller interface boundary is incorporated into the model. Size and shape of powder particles as well as roller rotational and linear velocities are considered within the friction coefficient. Powder bed parameters such as compaction pressure, stress distribution and relative density are predicted using the simulation.

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)0.001
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 score0.094
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.021
GPT teacher head0.228
Teacher spread0.207 · 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