Reliability of a Frailty Index Based on the Clinical Assessment of Health Deficits in Male C57BL/6J Mice
Bibliographic record
Abstract
We investigated the reliability of a newly developed clinical frailty index (FI) that measures frailty based on deficit accumulation in aging mice. FI scores were measured by two different raters independently in a large cohort (n = 233) of 343-430 day-old male C57BL/6J mice. Inter-rater reliability was evaluated with correlation coefficients, the kappa statistic, and intra-class correlation coefficients (ICC) in three separate groups of mice (n = 45, 50, and 138 mice/group) sequentially over 3 months. After each group was evaluated, descriptions of techniques used to identify health deficits were amended. Mice had comparable overall FI scores regardless of rater (0.213±0.002 vs 0.212±0.002; p = .802), although discordant measures declined as techniques were refined. Correlation coefficients (r (2) values) between raters improved throughout the study and mean kappa values increased (mean ± SEM; 0.621±0.018, 0.764±0.017, and 0.836±0.009 for groups 1, 2, and 3; p < .05). Values for intra-class correlation coefficient also improved from .51 (95% confidence interval = 0.11-.73) to .74 (0.54-0.85) and .77 (0.67-.83). FI scores increased over 3 months (p < .05), but did not differ between raters. These results show a high overall inter-rater reliability when the clinical FI tool is used to assess frailty in a large cohort of mice.
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How this classification was reachedexpand
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 | 0.008 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".