An experimental adaptive filtering system, built on the Okapi search engine, is described. In addition to the regular text retrieval functions, the system requires a complex set of procedures for setting score thresholds and adapting them following feedback. These procedures need to be closely related to the evaluation measures to be used. A mixture of quantitative methods relating a threshold to the number of documents expected to be retrieved in a time period, and qualitative methods relating to the probability of relevance, is defined. Experiments under the TREC-9 Adaptive Filtering Track rules are reported. The system is seen to perform reasonably well in comparison with other systems at TREC. Some of the variables that may affect performance are investigated.