MétaCan
Menu
Back to cohort
Record W3129389602 · doi:10.1002/9781119756743.ch3

Multiscale Methods for Lightweight Structure and Material Characterization

2021· other· en· W3129389602 on OpenAlexaff
Vincent Iacobellis, Kamran Behdinan

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEngineering
TopicComposite Material Mechanics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBridging (networking)Characterization (materials science)Multiscale modelingMaterials scienceComputer scienceNanocompositeBiological systemNanotechnology

Abstract

fetched live from OpenAlex

This chapter presents an overview of multiscale methods and their application to modeling in the design of lightweight materials and structures that demonstrate complex phenomena that span multiple spatial and temporal scales. A background on established methods found in the literature is provided with a focus on the bridging cell method (BCM) multiscale approach. The BCM formulation and its application in lightweight design is demonstrated through a review of past applications including fracture in single crystal metals, metal matrix nanocomposites, and polymer-matrix composite materials.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.603
Threshold uncertainty score0.995

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)0.0060.000

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 head0.007
GPT teacher head0.254
Teacher spread0.248 · 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.

Study designBench or experimental
Domainnot available
GenreMethods

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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicComposite Material MechanicsFrench-language works237,207