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Record W4292838683 · doi:10.1186/s12888-022-04194-6

Correction: Decomposing socioeconomic inequality in poor mental health among Iranian adult population: results from the PERSIAN cohort study

2022· erratum· en· W4292838683 on OpenAlexaff
Farid Najafi, Yahya Pasdar, Behzad Karami Matin, Satar Rezaei, Ali Kazemi Karyani, Shahin Soltani, Moslem Soofi, Shahab Rezaeian, Alireza Zangeneh, Mehdi Moradinazar, Behrooz Hamzeh, Zahra Jorjoran Shushtari, Mansour sajjadipour, Saeid Eslami, Maryam Khosrojerdi, Sahar Shabestari, Amir Houshang Mehrparvar, Zahra Kashi, Azim Nejatizadeh, Mohammadreza Naghipour, Shahrokh Sadeghi Boogar, Ali Fakhari, Bahman Cheraghian, Haydeh Heidari, Parviz Molavi, Mohammad Hajizadeh, Yahya Salimi

Bibliographic record

VenueBMC Psychiatry · 2022
Typeerratum
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Systems and Reforms
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPersianSocioeconomic statusMental healthCohort studyPsychologyCohortPopulationDemographyPsychiatryMedicineEnvironmental healthSociology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.009
metaresearch head score (Gemma)0.180
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.181
Threshold uncertainty score0.605

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.180
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0060.009
Science and technology studies0.0020.001
Scholarly communication0.0040.004
Open science0.0050.003
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.1810.043

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 head0.026
GPT teacher head0.277
Teacher spread0.250 · 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
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
Published2022
Admission routes1
Has abstractno

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