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Preface

2021· article· en· W4232526834 on OpenAlexaboutno aff

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2021
Typearticle
Languageen
FieldEngineering
TopicUnderground infrastructure and sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsPresentation (obstetrics)ChinaLibrary scienceArchitectureCoronavirus disease 2019 (COVID-19)PublishingSpace (punctuation)Political scienceGeographyEngineeringLawMedicineArchaeologyComputer science

Abstract

fetched live from OpenAlex

Associated research Centers for the Urban Underground Space (ACUUS) is an international, non-governmental organisation, promoting the sustainable use of the underground space. The ACUUS 2020 Virtual Conference took place in Helsinki, Finland on 3-4 February 2021 and was organized by the International organisation ACUUS, Finnish Tunnelling Association (MTR-FTA), Finnish Association of Architects (SAFA) and Finnish Association of Civil Engineers (RIL). The original dates for this conference were in September 2020. Due to covid-19 travel restrictions, the conference was postponed and it was arranged only virtually. Most of the scientific papers were received before summer holidays 2020 and it would have been unpleasant to postpone publishing these papers any longer. The conference included 96 presentations altogether. There were three categories of presentations: eight keynote speeches, 68 live presentations and 20 on demand video presentations. The keynotes represented current topics from the underground architecture to the latest developments in using underground space as well as the impact of the covid-19 Pandemic. The live presenters had 12 minutes time for presentation and then three minutes for Q/A. Moreover, 1400 chat messages were sent between participants during the conference. This publication consists of 51 accepted scientific papers under the following themes: Architecture Urban planning City development Underground infrastructures Design Reuse of underground space Sustainability and environment Geothermal energy Safety and human factors Perspectives Technical approaches and innovations The ACUUS 2020 conference had 195 participants from 24 countries. The participants in order of magnitude were from Finland, China, Japan, Hong Kong, Sweden, United States, Greece, Russia, United Kingdom, Singapore, Canada, Norway, Switzerland, Australia, Albania, Austria, Belgium, France, India, Iran, Israel, Italy, Serbia and Spain. The ACUUS 2020 conference was broadcasted in two parallel streams by ProspectumLIVE system. The papers were evaluated and reviewed by Ex-Ordo’s management system. The conference was considered very successful based on the participants’ feedback giving mean score of 4.3 (1 poor…5 excellent) for the overall conference experience and the overall technical quality mean score of 4.4. The ACUUS 2020 conference in Helsinki was the 17th in its history. The next conference will be held in Singapore in 2023. We want to take the opportunity to thank the authors of the published articles, the Scientific Committee members for their improving comments to the submitted papers in the review process and all active conference participants for interesting discussions during the sessions and breaks that contributed to the ACUUS 2020 Helsinki success. Editors Ilkka Vähäaho Chair of the ACUUS 2020 Scientific Committee Erik Johansson Co-chair of the ACUUS 2020 Scientific Committee

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)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.359
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0030.001
Scholarly communication0.0050.004
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.6410.482

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 head0.005
GPT teacher head0.176
Teacher spread0.171 · 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.

Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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