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Record W2962955971 · doi:10.32593/jstmu/vol2.iss1.40

Postural discomfort among right and left-handed University students of Rawalpindi and Islamabad.

2019· article· en· W2962955971 on OpenAlexaff
Benish Shahzadi, Sadaf Tareen, Syeda Hina Zahoor, Hamid Hussain, Malik Muhammad Ali, Hina Tariq

Bibliographic record

VenueJournal of Shifa Tameer-e-Millat University · 2019
Typearticle
Languageen
FieldMedicine
TopicMedical and Biological Sciences
Canadian institutionsRoyal University Hospital
Fundersnot available
KeywordsNoticeAudience measurementEditorial boardPolitical scienceQuality (philosophy)Public relationsLibrary scienceMedicineLawComputer science

Abstract

fetched live from OpenAlex

Retraction Notice: This article originally appeared in 1st issue of 2nd volume of the Journal of Shifa Tameer-e-Millat University (JSTMU), and has been marked as [RETRACTED]. The Editorial Board of JSTMU have re-examined the ancillary data/documents/attachments of the paper post-publication (on website) on receiving an “expression of concern” pertaining to conflict of interest among the authors. JSTMU follows (i) guidelines issued by the Committee on Publication Ethics (COPE), and (ii) editorial policies of the JSTMU, and takes the responsibility to enforce strict ethical policies and standards very seriously. To ensure the addition of high-quality scientific work and submission of genuine ancillary data/documents/attachments to the field of scholarly publications, the article titled “Postural discomfort among right and left-handed University students of Rawalpindi and Islamabad” bearing DOI No. https://doi.org/10.32593/jstmu/Vol2.Iss1.40 is retracted and shall be marked accordingly on all pre and post publication mediums of the journal. We apologize to the readership of JSTMU for any inconvenience caused.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.006
GPT teacher head0.214
Teacher spread0.208 · 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 designObservational
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

Citations0
Published2019
Admission routes1
Has abstractyes

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