Glacial isostatic adjustment (GIA) has a stabilizing effect on the evolution of the Antarctic ice sheet by reducing the grounding line migration following ice melt. The timescale and strength of this feedback depends on the spatially varying viscosity of the Earth's mantle. Most studies assume a relatively long and laterally homogenous response time of the bedrock. However, the mantle viscosity is spatially variable, with a high mantle viscosity beneath East Antarctica and a low mantle viscosity beneath West Antarctica. For this study, we have developed a new method to couple a 3D GIA model and an ice sheet model to study the interaction between the solid Earth and the Antarctic ice sheet during the last glacial cycle. With this method, the ice sheet model and GIA model exchange ice thickness and bedrock elevation during a fully coupled transient experiment. The feedback effect is taken into account with a high temporal resolution, where the coupling time steps between the ice sheet and GIA model are 5000 years over the glaciation phase and vary between 500 and 1000 years over the deglaciation phase of the last glacial cycle. During each coupling time step, the bedrock elevation is adjusted at every ice sheet model time step, and the deformation is computed for a linearly changing ice load. We applied the method using the ice sheet model ANICE and a 3D GIA finite element model. We used results from a regional seismic model for Antarctica embedded in the global seismic model SMEAN2 to determine the patterns in the mantle viscosity. The results of simulations over the last glacial cycle show that differences in mantle viscosity of an order of magnitude can lead to differences in the grounding line position up to 700gkm and to differences in ice thickness of the order of 2gkm for the present day near the Ross Embayment. These results underline and quantify the importance of including local GIA feedback effects in ice sheet models when simulating the Antarctic ice sheet evolution over the last glacial cycle.

The Antarctic mantle, bounded between the core and the Mohorovicǐćdiscontinuity, is one of the most difficult targets of study on Earth because of ice cover and rare outcrops. A multidisciplinary approach is adopted in this volume, using petrology, geochemistry, remote-sensed data and geodesy to characterize the Antarctic mantle. This characterization has application to rates of glacial isostatic adjustment, heat flow, sea-level rise and tectonics. It places the Antarctic mantle domain in a global framework on a scale not attempted before. In this chapter we review the historical development of mantle studies in Antarctica, outline current research directions, introduce the volume chapters and pro-vide a summary and outlook.

Rationale: This paper aims to show how the focus on eradicating bias from Machine Learning decision-support systems in medical diagnosis diverts attention from the hermeneutic nature of medical decision-making and the productive role of bias. We want to show how an introduction of Machine Learning systems alters the diagnostic process. Reviewing the negative conception of bias and incorporating the mediating role of Machine Learning systems in the medical diagnosis are essential for an encompassing, critical and informed medical decision-making. Methods: This paper presents a philosophical analysis, employing the conceptual frameworks of hermeneutics and technological mediation, while drawing on the case of Machine Learning algorithms assisting doctors in diagnosis. This paper unravels the non-neutral role of algorithms in the doctor's decision-making and points to the dialogical nature of interaction not only with the patients but also with the technologies that co-shape the diagnosis. Findings: Following the hermeneutical model of medical diagnosis, we review the notion of bias to show how it is an inalienable and productive part of diagnosis. We show how Machine Learning biases join the human ones to actively shape the diagnostic process, simultaneously expanding and narrowing medical attention, highlighting certain aspects, while disclosing others, thus mediating medical perceptions and actions. Based on that, we demonstrate how doctors can take Machine Learning systems on board for an enhanced medical diagnosis, while being aware of their non-neutral role. Conclusions: We show that Machine Learning systems join doctors and patients in co-designing a triad of medical diagnosis. We highlight that it is imperative to examine the hermeneutic role of the Machine Learning systems. Additionally, we suggest including not only the patient, but also colleagues to ensure an encompassing diagnostic process, to respect its inherently hermeneutic nature and to work productively with the existing human and machine biases.

Sea-level indicators dated to the Last Interglacial, or Marine Isotope Stage (MIS) 5e, have a twofold value. First, they can be used to constrain the melting of Greenland and Antarctic Ice Sheets in response to global warming scenarios. Second, they can be used to calculate the vertical crustal rates at active margins. For both applications, the contribution of glacio- and hydro-isostatic adjustment (GIA) to vertical displacement of sea-level indicators must be calculated. In this paper, we re-assess MIS 5e sea-level indicators at 11 Mediterranean sites that have been generally considered tectonically stable or affected by mild tectonics. These are found within a range of elevations of 2–10 m above modern mean sea level. Four sites are characterized by two separate sea-level stands, which suggest a two-step sea-level highstand during MIS 5e. Comparing field data with numerical modeling we show that (i) GIA is an important contributor to the spatial and temporal variability of the sea-level highstand during MIS 5e, (ii) the isostatic imbalance from the melting of the MIS 6 ice sheet can produce a >2.0 m sea-level highstand, and (iii) a two-step melting phase for the Greenland and Antarctic Ice Sheets reduces the differences between observations and predictions. Our results show that assumptions of tectonic stability on the basis of the MIS 5e records carry intrinsically large uncertainties, stemming either from uncertainties in field data and GIA models. The latter are propagated to either Holocene or Pleistocene sea-level reconstructions if tectonic rates are considered linear through time.