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Record W4385461258 · doi:10.1007/s42114-023-00724-2

Correction: Effective three-dimensional thermal conductivity networks in polystyrene/multi-walled carbon nanotubes/aluminum oxide@hexagonal boron nitride composites based on synergistic effects and isolated structures

2023· article· en· W4385461258 on OpenAlexaff
Zhengfang Wang, Zijian Wu, Najla AlMasoud, Ling Weng, Taghrid S. Alomar, Zeinhom M. El‐Bahy, Mingpeng He, Changjie Yang, Mingqi Sun, Priyanka Wasnik, Handong Li, Hassan Algadi, Sri Hari Kumar Annamareddy, Deepak Sridhar

Bibliographic record

VenueAdvanced Composites and Hybrid Materials · 2023
Typearticle
Languageen
FieldMaterials Science
TopicThermal properties of materials
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMaterials scienceCarbon nanotubeThermal conductivityComposite materialBoron nitridePolystyreneHexagonal boron nitrideHexagonal crystal systemOxideAluminiumBoron oxideNitrideCarbon fibersThermalNanotechnologyGraphenePolymerMetallurgyComposite numberCrystallographyChemistryLayer (electronics)

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.002
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.046
Threshold uncertainty score0.154

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.023
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0040.002
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0460.020

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 head0.220
Teacher spread0.213 · 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 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

Citations1
Published2023
Admission routes1
Has abstractno

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