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Additional file 1 of A case for improved assessment of gut permeability: a meta-analysis quantifying the lactulose:mannitol ratio in coeliac and Crohn’s disease

2022· article· en· W6901923546 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsnot available
Fundersnot available
KeywordsLactuloseCoeliac diseaseMean differenceSignificant differenceIntestinal permeability

Abstract

fetched live from OpenAlex

Additional file 1: Appendix 1: Search Strategy for gut permeability and lactulose mannitol test in disease in Medline. Appendix 2: Search Strategy for gut permeability and lactulose mannitol test in disease in Embase. Appendix 3: Search Strategy for gut permeability and lactulose mannitol test in disease in Cochrane. Figure S1: PRISMA 2009 Flow diagram for coeliac disease. Figure S2: PRISMA 2009 Flow diagram for Crohn’s disease. Figure S3A: Standard Mean Difference (SMD) in LMR between treated coeliac disease and healthy controls. Figure S3B: Weighted Mean Difference (WMD) in LMR between treated coeliac disease and healthy controls. Figure S3C: Standard Mean Difference (SMD) in LMR between untreated coeliac disease and healthy controls. Figure S3D: Weighted Mean Difference (WMD) in LMR between untreated coeliac disease and healthy controls. Figure S3E: Standard Mean Difference (SMD) in LMR between untreated and treated coeliac disease. Figure S3F: Weighted Mean Difference (WMD) in LMR between untreated and treated coeliac disease. Figure S4A: Standard Mean Difference (SMD) in LMR between healthy controls and inactive Crohn's disease. Figure S4B: Weighted Mean Difference (WMD) in LMR between healthy controls and inactive Crohn's disease. Figure S4C: Standard Mean Difference (SMD) in LMR between active Crohn's disease and healthy controls. Figure S4D: Weighted Mean Difference (WMD) in LMR between active Crohn's disease and healthy controls. Figure S4E: Standard Mean Difference (SMD) in LMR between active and inactive Crohn's disease. Figure S4F: Weighted Mean Difference (WMD) in LMR between active and inactive Crohn's disease. Figure S5: Sensitivity and specificity of the L:M test in coeliac disease. Figure S6: Risk of bias for each risk of bias item in RCT studies. Figure S7: Risk of bias assessments presented per risk of bias domain in RCT studies. Figure S8: Risk of bias for each risk of bias item in non-randomised and cohort studies. Figure S9: Risk of bias assessments presented per risk of bias domain in non-randomised and cohort studies. Table S1: Summary of studies of gut permeability in Crohn’s disease. Table S2: Summary of studies of gut permeability in coeliac disease. Table S3: Sources of variability for the studies included in the meta-analysis. Table S4: Studies depicting sensitivity and specificity of LMR in screening for coeliac disease. Table B1: Newcastle Ottawa Score Assessing Risk of Bias for Case Control Studies. Table B2: Newcastle Ottawa Score Assessing Risk of Bias for Cross Sectional Studies. Table B3: Risk of Bias for Randomised Control Trials (RCT) using the Cochrane Risk of Bias Tool. Table B4: Risk of Bias in non-randomised trials and cohort studies using the ROBINS-I score.

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)0.100
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: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.824
Threshold uncertainty score0.251

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.100
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.006
Bibliometrics0.0040.006
Science and technology studies0.0010.000
Scholarly communication0.0020.004
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.8240.044

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 head0.063
GPT teacher head0.320
Teacher spread0.257 · 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 designMeta-analysis
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
Published2022
Admission routes1
Has abstractyes

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