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Comment on “Ultrahigh Convergent Thermal Conductivity of Carbon Nanotubes from Comprehensive Atomistic Modeling”

2022· letter· en· W4283394320 on OpenAlexaff
Daniel Bruns, Alireza Nojeh, A. Srikantha Phani, Jörg Rottler

Bibliographic record

VenuePhysical Review Letters · 2022
Typeletter
Languageen
FieldMaterials Science
TopicThermal properties of materials
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCarbon nanotubeThermal conductivityMaterials scienceThermalCarbon fibersNanotechnologyChemical physicsThermodynamicsPhysicsComposite material

Abstract

fetched live from OpenAlex

Received 14 September 2021Accepted 23 May 2022DOI:https://doi.org/10.1103/PhysRevLett.128.259601© 2022 American Physical SocietyPhysics Subject Headings (PhySH)Research AreasPhononsThermal conductivityPhysical SystemsCarbon-based materialsNanotubesNanowiresTechniquesBoltzmann theoryMolecular dynamicsCondensed Matter, Materials & Applied Physics

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.033
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.021
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0020.003
Open science0.0040.001
Research integrity0.0330.027
Insufficient payload (model declined to judge)0.0100.014

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 head0.051
GPT teacher head0.275
Teacher spread0.224 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations5
Published2022
Admission routes1
Has abstractyes

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