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Record W6921010328 · doi:10.6084/m9.figshare.19144828

Additional file 1 of Adverse Effects of fine particulate matter on human kidney functioning: a systematic review

2022· article· en· W6921010328 on OpenAlexaboutno aff

Bibliographic record

VenueOpen MIND · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsConfoundingComparabilityAdverse effectHuman healthRisk assessmentHuman kidneyHuman studiesTable (database)

Abstract

fetched live from OpenAlex

Additional file 1: Supplementary Table 1. Risk of bias analysis performed according to the Newcastle-Ottawa scale. Crosses (×) indicate the allocation of a point in the scale; The minus sign (-) indicates the failure to accommodate the subject(s) discussed. Ascertainment of exposure checks the derivation of the exposure measurements (×) and the demonstration that the outcome of interest was not present at the start of the study (×). Comparability encompasses the presence of the main confounder age (×) and any additional confounder(s) (×) respectively. Articles were considered to have a high risk of bias below 4 points, a medium risk of bias below 6 points, and a low risk of bias above or equal to 6 points.

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)0.005
metaresearch head score (Gemma)0.076
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.804
Threshold uncertainty score0.280

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.076
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0070.011
Science and technology studies0.0010.000
Scholarly communication0.0020.004
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.8040.034

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 head0.045
GPT teacher head0.317
Teacher spread0.272 · 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.

Study designSystematic review
Domainnot available
GenreReview

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 abstractyes

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