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The Petiole of the Miriti Palm: A sustainable material for wind turbine blades?

2024· article· en· W4399489739 on OpenAlex
I. dos S. Gomes, Jerson Rogério Pinheiro Vaz, Jerome Wong, David Wood

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

VenueJournal of Physics Conference Series · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Management and Crop Yield
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPalmPetiole (insect anatomy)Ultimate tensile strengthTurbine bladeComposite materialMaterials scienceEnvironmental scienceHorticultureTurbinePulp and paper industryBotanyBiologyEngineeringMechanical engineeringPhysics

Abstract

fetched live from OpenAlex

Abstract The Miriti Palm (Mauritia flexuosa) grows abundantly in the Amazon Region of Brazil. The petiole (PMP) that supports the leaves, has a density of about one-half of Balsa wood (BW), which is used in the manufacture of wind turbine blades. A further possible advantage of PMP is that harvesting does not kill the palm tree, in contrast to the harvesting of BW. Because the mechanical properties of PMP have not been measured, we determined the shear and tensile properties of 16 samples of PMP and BW to allow a preliminary assessment of PMP as a possible material for blades. The absolute shear and tensile strengths for BW are higher, but specific properties (normalized by the density) are similar and can favour PMP. Direct substitution of BW by PMP would reduce the weight of a typical large blade by around 2%.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.268
Threshold uncertainty score0.271

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 head0.016
GPT teacher head0.217
Teacher spread0.201 · 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