Newcastle-Ottawa Scale: comparing reviewers’ to authors’ assessments
Bibliographic record
Abstract
BACKGROUND: Lack of appropriate reporting of methodological details has previously been shown to distort risk of bias assessments in randomized controlled trials. The same might be true for observational studies. The goal of this study was to compare the Newcastle-Ottawa Scale (NOS) assessment for risk of bias between reviewers and authors of cohort studies included in a published systematic review on risk factors for severe outcomes in patients infected with influenza. METHODS: Cohort studies included in the systematic review and published between 2008-2011 were included. The corresponding or first authors completed a survey covering all NOS items. Results were compared with the NOS assessment applied by reviewers of the systematic review. Inter-rater reliability was calculated using kappa (K) statistics. RESULTS: Authors of 65/182 (36%) studies completed the survey. The overall NOS score was significantly higher (p < 0.001) in the reviewers' assessment (median = 6; interquartile range [IQR] 6-6) compared with those by authors (median = 5, IQR 4-6). Inter-rater reliability by item ranged from slight (K = 0.15, 95% confidence interval [CI] = -0.19, 0.48) to poor (K = -0.06, 95% CI = -0.22, 0.10). Reliability for the overall score was poor (K = -0.004, 95% CI = -0.11, 0.11). CONCLUSIONS: Differences in assessment and low agreement between reviewers and authors suggest the need to contact authors for information not published in studies when applying the NOS in systematic reviews.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.543 | 0.853 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.014 | 0.022 |
| Bibliometrics | 0.033 | 0.025 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.010 | 0.010 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".