Classifying Broad Absorption Line Quasars: Metrics, Issues and a New
  Catalogue Constructed from SDSS DR5
  We apply a recently developed method for classifying broad absorption line
quasars (BALQSOs) to the latest QSO catalogue constructed from Data Release 5
of the Sloan Digital Sky Survey. Our new hybrid classification scheme combines
the power of simple metrics, supervised neural networks and visual inspection.
In our view the resulting BALQSO catalogue is both more complete and more
robust than all previous BALQSO catalogues, containing 3552 sources selected
from a parent sample of 28,421 QSOs in the redshift range 1.7<z<4.2. This
equates to a raw BALQSO fraction of 12.5%.
  In the process of constructing a robust catalogue, we shed light on the main
problems encountered when dealing with BALQSO classification, many of which
arise due to the lack of a proper physical definition of what constitutes a
BAL. This introduces some subjectivity in what is meant by the term BALQSO, and
because of this, we also provide all of the meta-data used in constructing our
catalogue, for every object in the parent QSO sample. This makes it easy to
quickly isolate and explore sub-samples constructed with different metrics and
techniques. By constructing composite QSO spectra from sub-samples classified
according to the meta-data, we show that no single existing metric produces
clean and robust BALQSO classifications. Rather, we demonstrate that a variety
of complementary metrics are required at the moment to accomplish this task.
Along the way, we confirm the finding that BALQSOs are redder than non-BALQSOs
and that the raw BALQSO fraction displays an apparent trend with
signal-to-noise, steadily increasing from 9% in low signal-to-noise data, up to
15%.
