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Record W4285164431 · doi:10.18690/um.fov.3.2022.17

Doživljanje epidemije COVID-19 med študenti

2022· article· en· W4285164431 on OpenAlexaboutno aff
Branko Gabrovec, Nuša Crnkovič, Andrej Šorgo, Katarina Cesar, Špela Selak, Ivana Kršić, Teja Tovornik, Vesna Paveo, Andraž Ajdič, Mitja Verdelja

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsAnxietyCoronavirus disease 2019 (COVID-19)PandemicQuarter (Canadian coin)Social mediaInsomniaMedicineCross-sectional studyPsychologyWeb surveyData collectionFamily medicinePsychiatryDiseaseGeography

Abstract

fetched live from OpenAlex

The aim of this study was to obtain data on the experience of the Covid-19 epidemic, related measures and changed living conditions of full time post-secondary Slovenian students. Data collection was conducted through a self-reported empirical web based survey as a part of a large cross-sectional study. Questionnaire was divided into 13 thematic sections. The survey took place between February 9 and March 8, 2021. A random sample consisted of 4,455 individuals. From the beginning of pandemic, the life has strongly changed 76% of survey participants, 56 % reported a change of daily rutine. In comparison to the time before the pandemic, they sleep more often, watch TV, use internet and social media, 17,6% reported decrease of financial safety. Only a quarter of survey participants reported that online study was successful. 23,3% reported fear of Covid-19, 4.7% acute clinical insomnia, severe depressive symptoms were present in 30,7 % of the respondents. severe anxiety symptoms in 16 % and 5% reported to have them almost every day suicidal thoughts The proportion of respondents who frequently sought psychological help increased during the epidemic.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.161
GPT teacher head0.508
Teacher spread0.347 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations2
Published2022
Admission routes1
Has abstractyes

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