Simulations of multiple mini-tip effects in STM images (that ignore electron interference effects) may be understood as modeling multiple mini-tip (or tip shape) effects in images that were recorded with other types of SPMs as long as the lateral sample feature sizes to be imaged are much larger than the effective scanning probe tip sizes.
Although the underlying physics of the IOA approach is specific to STM imaging, simulations of multiple-tip effects that ignore electron interference effects may be understood as modeling multiple mini-tip (or tip shape) effects in images that are recorded with other types of SPMs (where quantum mechanical interference effects can be safely ignored).
(3) and (4) are again to be understood as minimal models of fitness landscapes for binding sites, representing target sequence selection for a given level of binding (ρoff < r < ρon) and for sufficiently strong binding (r < ρon), respectively.
Although using artificial neurons as structural elements, Walknet, being a phenomenological model, should not be understood as a model describing the neuronal architecture itself, but as a quantitative, consistent hypothesis summarizing behavioral findings.
The Schrödinger equation can be understood as a model balancing a clustering force (represented by the potential V) and a dispersive force (the second derivative term), that it is responsible for the fact that the data are not concentrated at the minima of V (bottoms of the potential energy).
The consensus secondary structure of our dataset, generated with RNAsalsa, can be understood as a model parameter that defines site interactions and thus character dependence due to compensatory mutations [ 34, 82, 83].
The model that was proposed here has to be understood as a detailed model at the level of the kinetics of the cellular populations of a possible mechanism that might enable tumour cells to evade from the control of adaptive immunity.
(2011, see Section Prediction effects uncovered in the absence of stimulation: omission paradigms in the current paper), auditory perception can be understood as an internal model of the sensory input that is a result of a hierarchical cascade of prediction errors being compared with top-down predictions at different levels of the processing hierarchy.
Piccinini and Craver (2011) argue that such models should be understood as mechanistic sketches, black-box models to be evaluated and filled in as details about the underlying mechanism are discovered.
