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Record W4312400105 · doi:10.5944/bicim2022.034

Estimación numérica de las constantes elásticas de estructuras impresas en PLA y validación mediante ensayos experimentales

2022· article· es· W4312400105 on OpenAlex
Adrián Arias-Blanco, Miguel Marco, Ricardo Belda, María Henar Miguélez

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.

Bibliographic record

VenueCongreso Iberoamericano de Ingeniería Mecánica-CIBIM 2022 · 2022
Typearticle
Languagees
FieldEarth and Planetary Sciences
Topic3D Surveying and Cultural Heritage
Canadian institutionsCanadiana.org
Fundersnot available
KeywordsHumanitiesPhysicsPhilosophy

Abstract

fetched live from OpenAlex

La fabricacin aditiva o impresin 3D mediante deposicin de material fundido es una tcnica de fabricacin que presenta grandes ventajas, tales como la variabilidad de piezas que un mismo dispositivo puede fabricar/imprimir o la rapidez de diseo. No obstante, existe una brecha en el conocimiento del comportamiento mecnico de las estructuras impresas en 3D, dificultando la implantacin de estas en el entorno industrial. En este trabajo, se pretende analizar las propiedades mecnicas de estructuras obtenidas por fabricacin aditiva desde una escala mesoscpica, validando los resultados obtenidos mediante ensayos experimentales. Para ello, mediante modelos numricos de elementos finitos y homogeneizacin numrica de la respuesta elstica, se obtendrn las constantes elsticas de diferentes estructuras. Adems, se ha llevado a cabo la caracterizacin de estas estructuras mediante microtomografa computarizada,

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.502
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0020.002
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0200.000

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 head0.010
GPT teacher head0.259
Teacher spread0.249 · 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