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Record W4404762276 · doi:10.1002/smll.202470356

Highly Anisotropic Thermally Conductive Dielectric Polymer/Boron Nitride Nanotube Composites for Directional Heat Dissipation (Small 48/2024)

2024· article· en· W4404762276 on OpenAlexaff
Azadeh Zandieh, Piyapong Buahom, Elnaz Baradaran Shokouhi, Lun Howe Mark, Reza Rahmati, Omid Aghababaei Tafreshi, Mahdi Hamidinejad, Andreas Mandelis, Keun Su Kim, Chul B. Park

Bibliographic record

VenueSmall · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsNational Research Council CanadaUniversity of AlbertaUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceBoron nitrideComposite materialDielectricDissipationNanotubeThermal management of electronic devices and systemsElectrical conductorAnisotropyPolymerCarbon nanotubeOptoelectronics

Abstract

fetched live from OpenAlex

Dielectric Materials An aligned, flexible boron nitride nanotube surrounded by polycarbonate molecular chains demonstrates its effectiveness in directional heat transfer. In the background, a blurred hexagonal nanostructure signifies the nanotube's nanostructure. More in article number 2404189, Keun Su Kim, Chul B. Park, and co-workers.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.924

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 head0.228
Teacher spread0.212 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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
Published2024
Admission routes1
Has abstractyes

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