In May 2023, the authors’ paper ‘Schrödinger’s kittens – lifting the lid on resource drill hole data after mining’ (Moore et al, 2023), revealed an important aspect of resource estimation uncertainty that, although previously recognised, is typically overlooked. The paper presented a case study using closely spaced production gold assay data resurrected from OceanaGold’s mined-out Globe Progress deposit in New Zealand. The Globe Progress deposit was ‘redrilled’ 49 times at 35 m × 35 m spacings with an iterated moving point of origin (MPO) algorithm. There was found to be considerable spread across the 49 extracted drill hole sets (the Schrödinger effect), with eight of the 49 drill hole data sets not adequately representing the histogram of the in-ground mineralisation they were being used to estimate. Since the 2023 paper, four additional gold case studies from OceanaGold’s Waihi (New Zealand), Didipio (Philippines), Macraes (New Zealand) and Haile (USA) operating mines have been completed, confirming the original Globe Progress analysis. Given the reproducibility of the Schrödinger effect for the five case studies, the Schrödinger effect needs to be accepted as a fundamental component of resource estimation uncertainty, albeit not knowable until after mining. • Being an inherent property of the data, for a given drill spacing, the ‘Schrödinger effect’ represents the fundamental lower limit of estimation uncertainty. • For many estimates, the Schrödinger effect is the main driver of estimation uncertainty and therefore resource model performance. This data-related uncertainty, or ‘Schrödinger effect’, is a product of chance (luck of the draw) and because it is not knowable until after mining, presents the resource geologist with an invisible layer of uncertainty, prior to estimation. • This is problematic when attempting to quantify forward-looking estimation ranges. • The implications for resource classification are more layered and discussed in this paper. Surprisingly, the magnitude of the effect is similar across the five case studies despite diverse geological settings and mineralisation styles. This observation may help develop some ‘rules of thumb’. Building on the findings presented in the 2023 paper, this paper works through five case studies to explore the potential consequences stemming from the Schrödinger-effect; forward-looking estimation uncertainty, resource classification, model to mine reconciliation, as well as typical infill drill efficacy versus the surprisingly erratic outcomes of infill drilling on a campaign-by-campaign basis. MPO analysis is a powerful tool, operating in data-rich production environments, but is labour intensive and time-consuming. This provides fertile ground for existing and emerging technologies to streamline workflows.