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Record W3196060789 · doi:10.11159/mmme21.118

Evaluation of the Mechanical Behavior of Biomorphic Silicon CarbideDerived From Low-Density Peruvian Woods

2021· article· en· W3196060789 on OpenAlexvenueno aff
V.C. Bringas-Rodríguez, J.F. Gamarra-Delgado, M.L. Benavides-Salinas, Cris Katherin Palomino-Ñaupa, D.L. Mayta-Ponce, G.P. Rodríguez-Guillén, F.A. Huamán-Mamani

Bibliographic record

VenueProceedings of the World Congress on Mechanical, Chemical, and Material Engineering · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBamboo properties and applications
Canadian institutionsnot available
FundersConsejo Nacional de Ciencia, Tecnología e Innovación Tecnológica
KeywordsSilicon carbideMaterials scienceSiliconComposite materialEngineering physicsMetallurgyEngineering

Abstract

fetched live from OpenAlex

Low-density Peruvian woods (tornillo and bolaina) were used as raw material for the manufacture of biomorphic silicon carbide. The plant precursors were physically-mechanically characterized and then pyrolyzed at 900 C in an argon atmosphere to obtain carbon templates, which were then infiltrated with metallic silicon to obtain silicon carbide with mimicked microstructures. The values found for moisture absorption, basic density and average mechanical strength in uniaxial compression were 6.51%, 0.49 g/cm 3 and 42.5 MPa, respectively, for the tornillo and 6.99%, 0.42 g/cm 3 and 41.5 MPa, respectively, for the bolaina.

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.

How this classification was reachedexpand

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 score0.001
Threshold uncertainty score0.234

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 head0.019
GPT teacher head0.212
Teacher spread0.193 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

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