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Record W4210249882 · doi:10.22533/at.ed.903211207

Coleção desafios das engenharias: Engenharia de materiais e metalúrgica

2021· book· pt· W4210249882 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typebook
Languagept
FieldDecision Sciences
TopicBusiness and Management Studies
Canadian institutionsnot available
FundersUniversidade Estadual de Santa CruzCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsLibrary sciencePolitical scienceComputer science

Abstract

fetched live from OpenAlex

Environmental Stress Cracking (ESC), or simply stress cracking, is a phenomenon that occurs in polymeric materials when there is the joint action of a fluid (liquid or steam) with mechanical stresses, causing cracking or leading to premature and catastrophic failure of the material. The aim of this study is to investigate publications from the last 21 years (2000 to 2020) on stress cracking. The research was carried out in three databases, the Web of Science, Scielo and Scopus in order to obtain the number of articles published, verify which countries research the most on the subject, the related keywords and the main references adopted. With this, we highlight the routes built within this field in a timeline, as well as the main countries that assume leadership positions in these surveys. From the distribution of key words, it was found that there was a variation on the studies of the ESC phenomenon, such as: diversification in the polymers used and concern with not only mechanical, but also morphological and structural aspects. The surveys carried out in this study show that the annual amount of publications on the ESC phenomenon worldwide shows a discrete linear growth in the period from 2000 to 2020, and that Brazil is one of the main countries that research the phenomenon together with the USA, China , Germany and Canada.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.223
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0030.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1380.009

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 head0.122
GPT teacher head0.394
Teacher spread0.272 · 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; both teacher heads agree on what is shown here.

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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