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Record W6892314301 · doi:10.5061/dryad.5qfttdz8p

Data for: Inter-rater reliability of risk of bias tools for non-randomized studies

2024· dataset· en· W6892314301 on OpenAlexaffabout

Bibliographic record

VenueOpen MIND · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsIntraclass correlationReliability (semiconductor)ChecklistScale (ratio)Range (aeronautics)Measure (data warehouse)Point (geometry)

Abstract

fetched live from OpenAlex

PURPOSE: Currently, there is limited knowledge about the reliability of risk of bias (ROB) tools for assessing internal validity in systematic reviews of exposure and frequency studies. We aimed to identify and then compare the inter-rater reliability (IRR) of six commonly used tools for frequency (Loney scale, Gyorkos checklist, American Academy of Neurology [AAN] tool) and exposure (Newcastle-Ottawa scale, SIGN50 checklist, AAN tool) studies. METHODS: Six raters independently assessed the ROB of 30 frequency and 30 exposure studies using the 3 respective ROB tools. Articles were rated on a 3-level summary measure of ROB (low, intermediate, or high). We calculated an intraclass correlation coefficient (ICC) for each tool and category of ROB tool. We compared the IRR between ROB tools and tool type by inspection of overlapping ICC 95% CIs and by comparing their coefficients after transformation to Fisher Z values. We assessed criterion validity of the AAN ROB tools by calculating an ICC for each rater in comparison with the original ratings from the AAN. RESULTS: All individual ROB tools had an IRR in the substantial range or higher (ICC point estimate = 0.61-0.80). The IRR was almost perfect (ICC point estimate > 0.80) for the AAN frequency tool and the SIGN50 checklist. All tools were comparable in IRR, except for the AAN frequency tool which had a significantly higher ICC than the Gyorkos checklist (p=0.021) and trended towards a higher ICC when compared to the Loney scale (p=0.085). When examined by category of ROB tool, scales and checklists had a substantial IRR, whereas the AAN tools had an almost perfect IRR. For the criterion validity of the AAN ROB tools, the average agreement between our raters and the original AAN ratings was moderate. CONCLUSION: All tools had substantial IRR except for the AAN frequency tool and the SIGN50 checklist, which both had an almost perfect IRR. The AAN ROB tools were the only category of ROB tool to demonstrate an almost perfect IRR. This category of ROB tool had fewer and more simple criteria. Overall, parsimonious tools with clear instructions, such as those from the AAN, may provide more reliable ROB assessments.

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)0.417
metaresearch head score (Gemma)0.813
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.583
Threshold uncertainty score0.719

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4170.813
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0160.032
Bibliometrics0.0300.027
Science and technology studies0.0030.005
Scholarly communication0.0090.013
Open science0.0080.008
Research integrity0.0080.008
Insufficient payload (model declined to judge)0.0740.017

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 head0.242
GPT teacher head0.444
Teacher spread0.201 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainMethods
GenreDataset

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
Published2024
Admission routes2
Has abstractyes

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