MétaCan
Menu
Back to cohort
Record W2002473995 · doi:10.2174/157341311795542543

Are Carbon Nanotubes a Naturally Occurring Material? Hints from Methane CVD Using Lava as a Catalyst

2011· article· en· W2002473995 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCurrent Nanoscience · 2011
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCarbon nanotubeMaterials scienceRaman spectroscopyCatalysisScanning electron microscopeMethaneChemical engineeringChemical vapor depositionCarbon fibersNanomaterialsCarbon nanotube supported catalystNanotechnologyEnergy-dispersive X-ray spectroscopyCarbon nanofiberChemistryComposite materialOrganic chemistryComposite number

Abstract

fetched live from OpenAlex

Single-walled carbon nanotubes (SWNTs) were grown using methane CVD with lava as a catalyst and substrate. Metal-oxide phases embedded in the lava are reduced in the presence of hydrogen, thereby promoting catalytic growth. Scanning electron microscopy and energy-dispersive X-ray spectroscopy show a correlation between the growth of carbonaceous nanomaterials and the presence of iron in the alumina matrix. Raman spectroscopy of the carbon deposits proves the occurrence of SWNTs. Although this growth route lacks efficiency, it provides evidence for the claim that SWNTs are a natural allotrope of carbon and that volcanoes may provide an environment for their synthesis.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.012
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.001
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 head0.060
GPT teacher head0.297
Teacher spread0.237 · 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