physical sciences
physical sciences
In the physical sciences, and particularly fundamental research, describing the technical benefits of your study is a challenge in and of itself. Therefore, it’s common to forget to include a rigorous statement about your study limitations. Being transparent about one’s study design limitations is an important and expected part of any new research. In the physical sciences especially, the precise determination of a study’s limitations may be considered to be one of the strongest indicators of the author’s experience, as well as control over experimental constraints.
Iterate Your Study’s Focus
The key to aligning your description of study limitations with the reader’s expectations is to iterate the focus of your study’s aim. First, cite well-referenced principles and studies so that your reader can orient themselves before judging the rationale of your stated objectives and limitations that follow in-kind. Then, explicitly state the scope of your results to allow readers to immediately identify the relevance of your work to the current state of the field.
Adopt Precise Language
Unlike other research fields, which may sometimes adopt broad statements to encompass limitations regarding social demographics, applied context etc., the physical and pure sciences are in a position to make more precise, concrete references to known phenomena, approximations, models, sampling methods, scale effects, etc. In other words, uncertainties should apply only to the results themselves, not the language or description!
Examples in Papers on Physical Science
Below are two solid examples of how study limitations have been concisely stated in papers. The first is in reference to experimental constraints:
There are several limitations regarding the test methods used in this study. The flexural-strength test combined tensile, compressive, and shear stresses and included elements of proportional limit and elastic-modulus measurements [46]. A three-point bending test was performed to evaluate the flexural strength of the materials. However, due to the small size of the CAD-CAM blocks, specimen sizes that were described in ISO 6872:2015 [15] were modified, and, as a result, span length was shorter and test setup was miniaturized. To overcome the limitations of block sizes, a new method for assessing flexural strength was recently introduced that requires smaller test specimens with rectangular plate geometry [46]. This test method may be conducted in further studies. … Therefore, considering the limitations of the test methods used, the findings of this study may be regarded as initial mechanical characterization of the materials and may not be directly relevant to clinical conditions.
(Ongun et al., Materials 2018; doi: 10.3390/ma11091681)
In short, this precise description from the discussion of results serves to: 1) Refer to relevant physical phenomena and standard testing methodology; 2) Summarize the approach used in the study; 3) Identify the limitation and explain its cause; 4) Identify applicable workarounds; 5) Relate the results to the current field and real-world context.
The second is an example regarding model validation:
However, the main caveat of this study, like previous model intercomparison studies [6–8], is that the estimation of the accuracy of each model relies upon comparison of model projections with species presence and absence records. Each of the considered vegetation model selected in this study, projects the potential distribution of a species (even if correlative models are fitted on the species realised distribution) without considering factors such as dispersal abilities, complex biotic interactions or human activities which would explain the species present distribution. In addition, one has to note that the few databases of species distribution show major discrepancies even for common and widely distributed species such as F. sylvatica (Chuine et al., in prep). Therefore, the estimation of the model projections accuracy is highly dependent upon the reference database.
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