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Record W4386903279 · doi:10.23977/jemm.2023.080401

Research and Innovative Application of Biomimetic Tessellation Principles

2023· article· en· W4386903279 on OpenAlex
Mingyu Jin, Zichen Bai, Xiaosong Zhang

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Engineering Mechanics and Machinery · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced Theoretical and Applied Studies in Material Sciences and Geometry
Canadian institutionsnot available
Fundersnot available
KeywordsTessellation (computer graphics)Biomimetic materialsFlexibility (engineering)BiomimeticsStability (learning theory)NanotechnologyComputer scienceEngineeringBiological systemMaterials scienceMathematicsComputer graphics (images)BiologyMachine learning

Abstract

fetched live from OpenAlex

Biomimetic tessellation is the combination of biomimetic and tessellation principles. This paper conducted an in-depth study on those theory. First, the author introduced biomimetic pangolin scales and biomimetic aggregates fruit, and conducted a target study on their animal and plant morphology by using the biomimetic tessellation principle. Second, according to the advantages obtained, the author chooses a suitable building case and makes innovate application of two biomimetic tessellation principle to test its rationality. The conclusion shows that the two biomimetic tessellation principles can greatly improve the building in the aspects of shading, comfort, flexibility, stability, economy, etc., which provides ideas and directions for future research.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.753
Threshold uncertainty score0.168

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.018
GPT teacher head0.277
Teacher spread0.259 · 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