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Record W2065667361 · doi:10.1002/adma.200390009

Ceramics Containing Magnetic Co–Fe Alloy Nanoparticles from the Pyrolysis of a Highly Metallized Organometallic Polymer Precursor

2003· article· en· W2065667361 on OpenAlexaff
A. Berenbaum, Madlen Ginzburg-Margau, Neil Coombs, Alan J. Lough, Athena S. Sefat, John E. Greedan, Geoffrey A. Ozin, Ian Manners

Bibliographic record

VenueAdvanced Materials · 2003
Typearticle
Languageen
FieldMaterials Science
TopicElectromagnetic wave absorption materials
Canadian institutionsBrockhouse Institute for Materials ResearchMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceBimetallic stripSuperparamagnetismPyrolysisCeramicNanoparticleCobaltAlloyPolymerFerromagnetismChemical engineeringAmorphous solidMagnetic nanoparticlesComposite materialMagnetizationNanotechnologyMetallurgyOrganic chemistryMetalMagnetic field

Abstract

fetched live from OpenAlex

Lightweight magnetic ceramics containing bimetallic (Co–Fe) nanoparticles in an essentially amorphous C/SiC matrix have been prepared from the pyrolysis of a polyferrocenylsilane with pendant cobalt clusters. The Figure shows a TEM image of the ceramic material formed at 600 °C under N2. Superparamagnetic or ferromagnetic particles may be made, depending on the pyrolysis temperature.

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)0.000
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.012
GPT teacher head0.241
Teacher spread0.229 · 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

Citations75
Published2003
Admission routes1
Has abstractyes

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