MétaCan
Menu
Back to cohort
Record W2105783007 · doi:10.1111/ijac.12316

Effect of Gray Scale Binder Levels on Additive Manufacturing of Porous Scaffolds with Heterogeneous Properties

2014· article· en· W2105783007 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

VenueInternational Journal of Applied Ceramic Technology · 2014
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsUniversity of TorontoUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials sciencePorosityComposite materialLayer (electronics)

Abstract

fetched live from OpenAlex

An additive manufacturing platform was developed for fabricating constructs with heterogeneous properties. The liquid binder amount was investigated in calcium polyphosphate bone substitutes. Two part categories were produced with 150 and 190 μm layer thickness and 70, 80, 90, 100, and 90/70% gray scale. It was shown that the gray scale level had an effect on samples with 150 μm layer thickness where porosity ranged between 43 ± 1% and 49 ± 2% and the compressive strength varied between 4.8 ± 1.3 MP a and 15.5 ± 1.9 MP a. The results suggest that the binder gray scale level can be used to locally predict porous properties.

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 score0.255
Threshold uncertainty score0.573

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.004
GPT teacher head0.195
Teacher spread0.191 · 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