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Record W3023871379 · doi:10.1680/jenge.20.00054

Environmental geotechnics: challenges and opportunities in the post-Covid-19 world

2020· article· en· W3023871379 on OpenAlexafffund
Chao‐Sheng Tang, Evan K. Paleologos, Claudia Vitone, Yan‐Jun Du, Jiangshan Li, Ning‐Jun Jiang, Yongfeng Deng, Jian Chu, Zhengtao Shen, Eugeniusz Koda, Andrea Dominijanni, Xunchang Fei, Magdalena Daria Vaverková, Piotr Osiński, Xiaohui Chen, Afshin Asadi, Maria R.H. Takeuchi, Myint Win Bo, Hossam Abuel-Naga, Eng‐Choon Leong, Arvin Farid, Tuğçe Başer, Brendan C. O’Kelly, Bhagwanjee Jha, Venkata Siva Naga Sai Goli, Devendra Narain Singh

Bibliographic record

VenueEnvironmental Geotechnics · 2020
Typearticle
Languageen
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsUniversity of Alberta
FundersPolytechnique MontréalUniversidade de BrasíliaUniversità Politecnica delle MarcheArizona State University
KeywordsPandemicGeotechnicsEnvironmental planningEnvironmental resource managementCoronavirus disease 2019 (COVID-19)EngineeringEngineering ethicsEnvironmental scienceCivil engineeringInfectious disease (medical specialty)DiseaseMedicine

Abstract

fetched live from OpenAlex

The outbreak of the coronavirus disease 2019 (Covid-19) pandemic not only has created a health crisis across the world but is also expected to impact negatively the global economy and societies at a scale that is maybe larger than that of the 2008 financial crisis. Simultaneously, it has inevitably exerted many negative consequences on the geoenvironment on which human beings depend. The current paper articulates the role of environmental geotechnics in elucidating and mitigating the effects of the current pandemic. It is the belief of all authors that the Covid-19 pandemic presents not only significant challenges but also opportunities for the development of the environmental geotechnics field. This discipline should make full use of geoenvironmental researchers’ and engineers’ professional skills and expertise to look for development opportunities from this crisis, to highlight the irreplaceable position of the discipline in the global fight against pandemics and to contribute to the health and prosperity of communities, to serve humankind better. In order to reach this goal while taking into account the specificity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the uncertainty of its environmental effects, it is believed that more emphasis should be placed on the following research directions: pathogen–soil interactions; isolation and remediation technologies for pathogen-contaminated sites; new materials for pathogen-contaminated soil; recycling and safe disposal of medical wastes; quantification of uncertainty in geoenvironmental and epidemiological problems; emerging technologies and adaptation strategies in civil, geotechnical and geoenvironmental infrastructures; pandemic-induced environmental risk management; and modelling of pathogen transport and fate in geoenvironment, among others. Moreover, Covid-19 has made it clear to the environmental geotechnics community the importance of urgent international co-operation and of multidisciplinary research actions that must extend to a broad range of scientific fields, including medical and public health disciplines, in order to meet the complexities posed by the Covid-19 pandemic.

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)0.006
metaresearch head score (Gemma)0.004
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.008
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0040.009
Scholarly communication0.0080.009
Open science0.0010.006
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.042
GPT teacher head0.197
Teacher spread0.155 · 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
GenreCommentary

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

Citations41
Published2020
Admission routes2
Has abstractyes

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