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General practice registrars in Australia undertake most of their vocational training in accredited general practices. They typically see patients alone from the start of their community-based training and are expected to seek timely ad hoc support from their supervisor. Such ad hoc encounters are a mechanism for ensuring patient safety, but also provide an opportunity for learning and teaching. Wenger's (Communities of practice: learning, meaning, and identity. Cambridge University Press, New York, 1998) social theory of learning ('communities of practice') guided a secondary analysis of audio-recordings of ad hoc encounters. Data from one encounter is re-presented as an extended sequence to maintain congruence with the theoretical perspective and enhance vicariousness. An interpretive commentary communicates key features of Wenger's theory and highlights the researchers' interpretations. We argue that one encounter can reveal universal understandings of clinical supervision and that the process of naturalistic generalisation allows readers to transfer others' experiences to their own contexts. The paper raises significant analytic, interpretive, and representational issues. We highlight that report writing is an important, but infrequently discussed, part of research design. We discuss the challenges of supporting the learning and teaching that arises from adopting a socio-cultural lens and argue that such a perspective importantly captures the complex range of issues that work-based practitioners have to grapple with. This offers a challenge to how we research and seek to influence work-based learning and teaching in health care settings.

The revised Bethesda guidelines are inadequate for LS screening when personal and family cancer history is not available to the pathologist, a universal screening paradigm greatly increased the rate of MSI testing and MSI-H CRC detection and CRCs less likely to be screened for LS were those diagnosed in locally excised specimens.

We describe an algorithm for application of the classic “drizzle” technique to produce 3D spectral cubes using data obtained from the slicer-type integral field unit (IFU) spectrometers on board the James Webb Space Telescope. This algorithm relies upon the computation of overlapping volume elements (composed of two spatial dimensions and one spectral dimension) between the 2D detector pixels and the 3D data cube voxels, and is greatly simplified by treating the spatial and spectral overlaps separately at the cost of just 0.03% in spectrophotometric fidelity. We provide a matrix-based formalism for the computation of spectral radiance, variance, and covariance from arbitrarily dithered data and comment on the performance of this algorithm for the Mid-Infrared Instrument’s Medium Resolution IFU Spectrometer. We derive a series of simplified scaling relations to account for covariance between cube spaxels in spectra extracted from such cubes, finding multiplicative factors ranging from 1.5–3 depending on the wavelength range and kind of data cubes produced. Finally, we discuss how undersampling produces periodic amplitude modulations in the extracted spectra in addition to those naturally produced by fringing within the instrument; reducing such undersampling artifacts below 1% requires a four-point dithering strategy and spectral extraction radii of 1.5 times the point-spread function FWHM or greater.

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