MétaCan
Menu
Back to cohort
Record W3152167827 · doi:10.1039/9781839162480-00296

3D Graphene-based Macrostructures as Superabsorbents for Oils and Organic Solvents

2021· book-chapter· en· W3152167827 on OpenAlexaff
Nariman Yousefi

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsNanotechnologyEnvironmentally friendlyOil spillBiochemical engineeringGrapheneMaterials scienceEnvironmental sciencePetroleum engineeringEngineeringEcology

Abstract

fetched live from OpenAlex

With frequent occurrence of oil spill incidents and accidental leakage of organic solvents, the development of highly efficient and environmentally friendly absorbents with both hydrophobic and oleophilic properties have become a top priority. This chapter collates the current state-of-the-art on the development and application of ultralight and mechanically resilient 3D GBMs for the selective absorption of a broad variety of oils and organic solvents, with an emphasis on underlying mechanisms. Furthermore, it highlights the fundamental knowledge gaps in the domain and lays out novel strategic research guidelines, all of which would promote further progress in this rapidly evolving cross-disciplinary field of current global interest.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.398
Threshold uncertainty score1.000

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)0.0230.000

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 head0.021
GPT teacher head0.249
Teacher spread0.228 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicSurface Modification and SuperhydrophobicityFrench-language works237,207