MétaCan
Menu
Back to cohort
Record W4409167438 · doi:10.1039/d4ee05328a

Polymeric membranes in carbon capture, utilization, and storage: current trends and future directions in decarbonization of industrial flue gas and climate change mitigation

2025· article· en· W4409167438 on OpenAlexafffund
Arash Mollahosseini, Mostafa Nikkhah Dafchahi, Saeed Khoshhal Salestan, Jia Wei Chew, Mohammad Mozafari, Masoud Soroush, Sabahudin Hrapovic, Usha D. Hemraz, Ronaldo Giro, M. Steiner, Young‐Hye La, Seyed Fatemeh Seyedpour Taji, Khalid Azyat, Sajjad Kavyani, Xinyu Wang, Jae‐Young Cho, Mohtada Sadrzadeh

Bibliographic record

VenueEnergy & Environmental Science · 2025
Typearticle
Languageen
FieldEngineering
TopicMembrane Separation and Gas Transport
Canadian institutionsNational Research Council CanadaUniversity of AlbertaUniversity of SaskatchewanMacEwan UniversityNational Institute for Nanotechnology
FundersOffice of Energy Research and DevelopmentNatural Resources CanadaCanada's Oil Sands Innovation AllianceNatural Sciences and Engineering Research Council of CanadaDivision of Civil, Mechanical and Manufacturing InnovationGovernment of CanadaNational Science Foundation
KeywordsClimate changeFlue gasCarbon capture and storage (timeline)Environmental scienceCurrent (fluid)Carbon fibersClimate change mitigationGreenhouse gasWaste managementMaterials scienceEngineeringGeologyOceanography

Abstract

fetched live from OpenAlex

Material, process, and computational developments for polymeric membrane-assisted decarbonization.

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.011
GPT teacher head0.223
Teacher spread0.211 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations95
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueEnergy & Environmental ScienceSame topicMembrane Separation and Gas TransportFrench-language works237,207