The Petermann Orogeny is a late Neoproterozoic to Cambrian (c. 560–520 Ma) intracratonic event that affected the Musgrave Block and south‐western Amadeus Basin in central Australia. In the Mann Ranges, within the central Musgrave Block, Mesoproterozoic granulite facies gneisses, granites and mafic dykes have been substantially reworked by deep crustal non‐coaxial strain of late Neoproterozoic to early Cambrian age. Dolerite dykes have recrystallized to garnet granulite facies assemblages, associated with the development of a mylonitic fabric at P=12–13 kbar and T =700–750 °C. Migmatization is restricted to discrete shear zones, which represent conduits for hydrous fluids during metamorphism. Peak metamorphism was followed by decompression to c. 7 kbar, reflecting exhumation of the terrane along the south‐dipping Woodroffe Thrust. In scattered outcrops north of the Mann Ranges, peak metamorphism occurred at P=9–10 kbar and T =c. 700 °C. The Woodroffe Thrust separates these deep crustal mylonites from granites that were metamorphosed during the Petermann Orogeny at P=c. 6–7 kbar and T =c. 650 °C. The similarity in peak temperatures at different crustal levels implies an unusual thermal regime during this event. The existence of a relatively elevated geotherm corresponding with Th‐ and K‐enriched granites that were in the mid‐crust during the Petermann Orogeny suggests that radiogenic heat production may have substantially contributed to the thermal regime during metamorphism. This potentially has implications for the mechanisms by which intra‐plate strain was localized during this event.

Background: This study was undertaken to develop a simple tool for assessing risk of undernutrition for use by the primary health care team. Methods: We devised a list of 25 questions that might be predictive of nutritional risk. Community nurses administered the questions, which required only yes/no answers, to 507 patients in their care. Within 4 days a dietitian carried out a full nutritional assessment. Discriminant analysis was used to determine which questions were predictive of nutritional risk as assessed by a dietitian. Multiple regression analysis was used to derive a simple equation to assign weightings to those questions. Results: Five hundred and seven patients completed the study. Nine questions were found to be associated with nutritional risk as assessed by a dietitian. The final tool, which has three categories of scores: 0–6=not at risk; 7–16=possible/probable risk; 517=malnourished, has a positive predictive value of 94.6% and a negative predictive value of 81.1%. Conclusion: This simple tool can be used to assess risk of undernutrition in patients in primary care, to increase awareness of the importance of nutrition in patients in the community and to ensure that patients are given appropriate dietary advice and/or referred to a dietitian.

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