In this study, we demonstrate how supervised learning can extract interpretable survey motivation measurements from a large number of responses to an open-ended question. We manually coded a subsample of 5,000 responses to an open-ended question on survey motivation from the GESIS Panel (25,000 responses in total); we utilized supervised machine learning to classify the remaining responses. We can demonstrate that the responses on survey motivation in the GESIS Panel are particularly well suited for automated classification, since they are mostly one-dimensional.
View Article and Find Full Text PDFTime-resolved rheology, small angle X-ray scattering (SAXS), and electron paramagnetic resonance (EPR) techniques were used to study the polymerization of geopolymers. These polymers are inorganically synthesized by the alkaline activation of an aluminosilicate source (metakaolin) in aqueous solution. The influence of the alkali activator (Na(+), K(+), and Cs(+)) was investigated at room temperature.
View Article and Find Full Text PDFHuman prolactin (HPr), luteinizing hormone (LH), follicle-stimulating hormone (FSH), testosterone, 5 alpha-dihydrotestosterone (DHT), oestrone and oestradiol are measured by radioimmunoassay (RIA) and bilogical prolactin activity additionally by pigeon crop sac assay in plasma of patients with prostatic carcinoma and two control groups. Pigeon crop sac assay is more often positive in cancer patients (50%) than in controls (20%) and HPr distinctly elevated in 20% of the carcinoma patients. Patients are classified according to histological type of tumour: carcinomas with cribriform and/or solid growth show significantly elevated pigeon crop sac activity and higher testosterone, DHT and oestrone levels in plasma than tumours without such growth.
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