Anne-Marie Robinson

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We present an incremental Bayesian model that resolves key issues of crowd size and data quality for consensus labeling. We evaluate our method using data collected from a real-world citizen science program, B<scp>ee</scp>W<scp>atch</scp>, which invites members of the public in the United Kingdom to classify (label) photographs of bumblebees as one of 22(More)
This paper explores the use of Natural Language Generation (NLG) for facilitating the provision of feedback to citizen scientists in the context of a nature conservation programme, BEEWATCH. BEEWATCH aims to capture the distribution of bumblebees, an ecologically and economically important species group in decline, across the UK and beyond. The NLG module(More)
Although influenza may cause fatal neonatal infections, the current prevalence of disease in newborn intensive care units (NICU) is unknown. Furthermore, because compliance of NICU staff with annual influenza immunization is poor, absence of antibody may provide an indication of influenza susceptibility for neonatal patients and staff. We studied our NICU(More)
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