MétaCan
Menu
Back to cohort
Record W4411656888 · doi:10.51847/oqwec9ewg4

10.51847/oqwec9ewG4

2000· article· en· W4411656888 on OpenAlexvenueno aff

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAddictionPsychological distressThe InternetPsychologyDistressClinical psychologyApplied psychologyPsychiatryMental healthComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

The present study is an attempt to assess internet addiction and psychological distress among university students.The sample in the study consisted of one hundred university students out of which 61 were males and 39 were females who were selected on the purposive basis from the main campus of Kashmir University.Young's Internet Addiction Scale (IAT), Kessler Psychological Distress Scale (K10) and Demographic Data sheet were used to collect research data from informants.The obtained data were analysed by frequency method, Pearson correlation method and t-test.The results revealed that male university students experienced more internet addiction and psychological distress as compared to the female university students and a significant positive correlation was found between internet addiction and psychological distress among university students.Moreover, the results also indicated that rural university students experienced more internet addiction and psychological distress as compared to urban university students.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.049
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.9510.918

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 head0.019
GPT teacher head0.159
Teacher spread0.140 · 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; the direct Gemma label and the distilled Codex classifier 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

Citations10
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueTime to knitSame topicDiverse Scientific and Economic StudiesFrench-language works237,207