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Record W3208259726 · doi:10.1016/j.xinn.2021.100180

Technologies and perspectives for achieving carbon neutrality

2021· review· en· W3208259726 on OpenAlexaff
Fang Wang, Jean Damascene Harindintwali, Zhizhang Yuan, Min Wang, Faming Wang, Sheng Li, Zhigang Yin, Lei Huang, Yuhao Fu, Lei Li, Scott X. Chang, Linjuan Zhang, Jörg Rinklebe, Zuoqiang Yuan, Qinggong Zhu, Leilei Xiang, Daniel C.W. Tsang, Liang Xu, Xin Jiang, Jihua Liu, Ning Wei, Matthias Kästner, Yang Zou, Yong Sik Ok, Jianlin Shen, Dailiang Peng, Wei Zhang, ‪Damià Barceló, Yongjin J. Zhou, Zhaohai Bai, Boqiang Li, Bin Zhang, Ke Wei, Hujun Cao, Zhiliang Tan, Liu‐Bin Zhao, Xiao He, Jinxing Zheng, Nanthi Bolan, Xiaohong Liu, Changping Huang, Sabine Dietmann, Ming Luo, Nannan Sun, Jirui Gong, Yulie Gong, Ferdi Brahushi, Tangtang Zhang, Cunde Xiao, Xianfeng Li, Wenfu Chen, Nianzhi Jiao, Johannes Lehmann, Yong‐Guan Zhu, Hongguang Jin, Andreas Schäffer, James M. Tiedje, Jing M. Chen

Bibliographic record

VenueThe Innovation · 2021
Typereview
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsUniversity of TorontoDalhousie UniversityUniversity of Alberta
FundersNational Key Research and Development Program of ChinaYouth Innovation Promotion Association of the Chinese Academy of SciencesNatural Science Foundation of Jiangxi ProvinceYulin UniversityChinese Academy of SciencesDalian National Laboratory for Clean EnergyNational Natural Science Foundation of ChinaNatural Science Foundation for Distinguished Young Scholars of Hunan ProvinceDeutsche ForschungsgemeinschaftMichigan State UniversityAlexander von Humboldt-Stiftung
KeywordsCarbon neutralityGreenhouse gasNatural resource economicsClimate changeFossil fuelClimate change mitigationSustainabilityEnvironmental scienceGlobal warmingRenewable energyCarbon sequestrationEnvironmental resource managementEngineeringEcologyEconomicsWaste managementCarbon dioxide

Abstract

fetched live from OpenAlex

from the atmosphere. Herein, we review innovative technologies that offer solutions achieving carbon (C) neutrality and sustainable development, including those for renewable energy production, food system transformation, waste valorization, C sink conservation, and C-negative manufacturing. The wealth of knowledge disseminated in this review could inspire the global community and drive the further development of innovative technologies to mitigate climate change and sustainably support human activities.

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)0.001
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 score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.002

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 head0.090
GPT teacher head0.375
Teacher spread0.285 · 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

Citations1,289
Published2021
Admission routes1
Has abstractyes

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