Inter‐rater reliability of h‐index scores calculated by Web of Science and Scopus for clinical epidemiology scientists
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: We investigated the inter-rater reliability of Web of Science (WoS) and Scopus when calculating the h-index of 25 senior scientists in the Clinical Epidemiology Program of the Ottawa Hospital Research Institute. MATERIALS AND METHODS: Bibliometric information and the h-indices for the subjects were computed by four raters using the automatic calculators in WoS and Scopus. Correlation and agreement between ratings was assessed using Spearman's correlation coefficient and a Bland-Altman plot, respectively. RESULTS: Data could not be gathered from Google Scholar due to feasibility constraints. The Spearman's rank correlation between the h-index of scientists calculated with WoS was 0.81 (95% CI 0.72-0.92) and with Scopus was 0.95 (95% CI 0.92-0.99). The Bland-Altman plot showed no significant rater bias in WoS and Scopus; however, the agreement between ratings is higher in Scopus compared to WoS. CONCLUSION: Our results showed a stronger relationship and increased agreement between raters when calculating the h-index of a scientist using Scopus compared to WoS. The higher inter-rater reliability and simple user interface used in Scopus may render it the more effective database when calculating the h-index of senior scientists in epidemiology.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.070 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.005 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it