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Record W2046727917 · doi:10.1039/c4ta06415a

Carbon-coated α-Fe<sub>2</sub>O<sub>3</sub> nanostructures for efficient anode of Li-ion battery

2015· article· en· W2046727917 on OpenAlexaff
Xiaoxin Lv, Jiujun Deng, Jian Wang, Jun Zhong, Xuhui Sun

Bibliographic record

VenueJournal of Materials Chemistry A · 2015
Typearticle
Languageen
FieldEnergy
TopicIron oxide chemistry and applications
Canadian institutionsCanadian Light Source (Canada)Saskatoon Medical ImagingUniversity of Saskatchewan
Fundersnot available
KeywordsAnodeMaterials scienceCarbon fibersIonBattery (electricity)NanostructureChemical engineeringNanotechnologyElectrodeChemistryComposite materialComposite numberPhysical chemistryPhysicsEngineering

Abstract

fetched live from OpenAlex

Carbon-coated hematite nanostructures were prepared for Li-ion battery with high capacity, and the mechanism was probed by scanning transmission X-ray microscopy.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.002
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.013
GPT teacher head0.229
Teacher spread0.215 · 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.

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

Citations69
Published2015
Admission routes1
Has abstractyes

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