<|begin_of_text|><|start_header_id|>system<|end_header_id|>

You are an expert at identifying data availability statements in scientific text. A data availability statement describes where research data can be found or how it can be accessed.<|eot_id|><|start_header_id|>user<|end_header_id|>

Determine if the following text contains a data availability statement. Answer with 'yes' or 'no'.

Text: The novel biomarker ki:e SB-C was systematically evaluated to determine fit for purpose by following the V3 framework. One important aspect and strength of digital biomarkers in general, and ki:e SB-C in particular, is automation. Speech **data** can be easily collected by telephone or by mobile front-ends face-to-face, and ki:e SB-C can be reliably calculated using the proprietary automatic speech analysis pipeline. Verification step of this study revealed that the automatic speech processing pipeline, including speech recognition, performs at an acceptable level across different languages and tasks, and therefore, automatic processing works reliably for the purposes of  the biomarker. The aim of the analytical validation was threefold: to evaluate (1) the ki:e SB-C against a cognitive gold standard measure (MMSE), (2) the biomarker's retest reliability, and (3) how well ki:e SB-C reflects agerelated -but clinically not relevant -changes. The results of the analytical validation analyses revealed that ki:e SB-C was a valid biomarker to measure cognitive abilities that are relevant for the target population, as seen by its high correlation with MMSE scores even if corrected for the effect of age. Furthermore, the automatically calculated biomarker was stable in retesting as assessed by a test-retest analysis. It is well established that aging is a risk factor for cognitive decline and diseases [26]; however, not all changes are pathological. It is important for a biomarker that is a surrogate for cognition to reflect subtle changes that are at a subclinical level. Our results showed that ki:e SB-C can detect age-related changes in cognitive function. These changes are also reflected in MMSE scores as a trend. Regarding the direct comparison with the MMSE on the healthy DeepSpA population, the SB-C seems to vary more marked by a larger standard deviation (regarding the mean) as compared to the MMSE. This might be also due to the fact that the SB-C is a more fine-grained measure as compared to the MMSE, which might especially in the healthy population lack the resolution to measure cognitive changes at this higher functioning level and would elicit less variance.<|eot_id|><|start_header_id|>assistant<|end_header_id|>

no<|eot_id|>