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Record W2564837236 · doi:10.31661/gmj.v5i4.786

A Cohort Study Protocol of Low Back Pain In Rural Area Inhabitants: Fasa Low Back Pain Cohort Study (FABPACS)

2016· article· en· W2564837236 on OpenAlexaboutno aff
Mojtaba Farjam, Alireza Askari, Ali Hoseinipour, Reza Homayounfar, Javad Jamshidi, Fatemeh Khodabakhshi, Habib Zakeri

Bibliographic record

VenueGalen Medical Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCohortLow back painAnthropometryPhysical therapyCohort studyPopulationSocioeconomic statusAlternative medicineInternal medicineEnvironmental healthPathology

Abstract

fetched live from OpenAlex

Background: Low back pain (LBP) is one of the main causes of disability in most societies that imposes much cost to the economic and health systems. In Iranian population, a prevalence as high as 27% has been reported for chronic LBP. So this study was designed to investigate the factors associated with low back pain in Iranian population. Methods/ Design: In Fasa Cohort Study, a branch of Persian cohort study, LBP patients were registered among the participants. A total of 10000 peoples, 1700 patients enrolled in cohort study were registered as LBP patients. In addition to detailed demographic, socioeconomic, anthropometric, nutrition, and medical history, limited physical examinations, determination of physical activity and body composition that was obtained in the cohort study, history of LBP, assessment of the pain severity, McGill pain inventory, and Oswestry questionnaire was filled for the LBP patients. All data are stored online using a dedicated software. Discussion: The cohort study is the best way to collect the necessary information required for policy making in the field of LBP. This study will help in providing some information about LBP in our area to establish a better management of the disease. Moreover, this study will provide many opportunities for clinical trials in this field, and we are going to do interventional studies in the cohort in future.[GMJ.2016;5(4):225-29]

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)0.026
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0260.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.000

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 head0.010
GPT teacher head0.301
Teacher spread0.291 · 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 teacher head, not a consensus.

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

Citations5
Published2016
Admission routes1
Has abstractyes

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