Data interpretation context dependence

Labels are distinguished based on whether they are context dependent or context-free. Context-dependent labels require simultaneous consideration of time records from more than one process variable context-free labels do not. Thus, generating context-free trend, landmark, and fault descriptions is considerably more simple than generating context-dependent descriptions. Context-free situations can take advantage of numerous methods for common, yet useful, interpretations. Context-dependent situations, however, require the application of considerable process knowledge to get a useful interpretation. In these situations, performance is dependent on the availability, coverage, and distribution of labeled process data from... 

Topical exposure to organophosphate (OP) and carbamate (CM) pesticides remains an important route for exposure to humans and animals. As in many subdisciplines in toxicology and other sciences, interpretation of pesticide deniial absorption data is highly dependent on the model systems u.sed to generate the data. This chapter discusses studies of pesticide absorption in the context of the experimental and theoretical approaches used to assess absorption, This field was reviewed by Baynes and Riviere (2001). which should be consulted for further details. This review highlighted the overarching importance of experimental design and subsequent interpretation of pesticide data reported in the literature since these factors often overshadow differences in absorption and subsequent toxicity between individual pesticides,... 

Analytical results are often represented in a data table, e.g., a table of the fatty acid compositions of a set of olive oils. Such a table is called a two-way multivariate data table. Because some olive oils may originate from the same region and others from a different one, the complete table has to be studied as a whole instead as a collection of individual samples, i.e., the results of each sample are interpreted in the context of the results obtained for the other samples. For example, one may ask for natural groupings of the samples in clusters with a common property, namely a similar fatty acid composition. This is the objective of cluster analysis (Chapter 30), which is one of the techniques of unsupervised pattern recognition. The results of the clustering do not depend on the way the results have been arranged in the table, i.e., the order of the objects (rows) or the order of the fatty acids (columns). In fact, the order of the variables or objects has no particular meaning. 

Due to the second criterion, time-to-tumor models were eliminated from consideration. These models require more detailed experimental data than is generally available. Moreover, it is difficult and unproductive to interpret the distribution of time-to-tumor in the context of human exposures. In most cases, the time-to-tumor variable would be integrated over a human lifetime, thus reducing the model to a purely dose-dependent one. Therefore we restrict our attention to quantal response models that estimate lifetime risks. 

Data quality is a broad, often loosely defined term. There are many problem- and discipline-related definitions to be found in the literature. This section shall not try to define data quality in any comprehensive, far less complete sense - suffice to denounce any definition that does not include the specific aspect of sample representativity however. Data is often equated with information, but this can only be in a hidden, potential form. Only data analysis together with interpretation may reveal information - which will always be in a particular problem-specific context only. Such issues are not usually seen as problematic in chemometrics and in PAT, where the pre-history of a data table ( data ) in general receives but scant attention. One relevant, major exception is Martens and Martens (2001) [26] who focus comprehensively on Multivariate Analysis of Quality . But even here there is a narrow focus on quality of information only, defined as ... dependent on reliability and relevance , without further clarifying the definition of these open-ended adjectives. 

Some important assays commonly used in biochemical genetics laboratories do not provide quantitative data (e.g. MPS-EP, qualitative urinary organic acid analysis, AA-TLC). In addition, all successful investigations depend heavily upon selection of the correct analytes to measure and the appropriate interpretation of the quantitative or qualitative results in their clinical context. These challenges suggest a requirement for external quality assessment or proficiency testing schemes that can inform participants about their performance in these areas when compared with other centres. 

Our ability to interpret the risks associated with biomonitoring findings depends on our knowledge of exposure, toxicologic, pharmacokinetic, and epidemiologic data of particular chemicals, as illustrated by the framework in Table 3-1. To interpret biomonitoring data better in the context of... 

Absolute versus relative values. In relational databases, the data values are often readily interpretable. For example, age is 35 is well understood. However, in image databases, the data values (e.g., pixel intensities) have a significance that will depend on the context. For example, a gray-scale value of 46 could appear darker than a gray-scale value of 87 if the surrounding context pixels values are all very bright. 

Several distinct energy loss peaks appear within the MgO band gap (between 1 and 5.5eV energy loss [218]) as a function of cluster size. These loss peaks cannot be assigned to low-lying transitions in the atom or in the ion [103,208,219,220]. EEL spectra of vapor deposited Ag, which forms islands and thin films via surface diffusion at sample temperatures between T = 100 and 500 K, have shown losses at 3.8 and 3.2 eV attributed to an Ag surface plasmon and to an Ag-MgO interface plasmon, respectively [218]. In contrast, the EEL spectra shown in Fig. 1.44 and recorded at T = 45K exhibit clearly a size dependence, which reflects the change in the electronic structure of the clusters. A similar behavior has been observed in optical absorption spectra of Ag (n < 21) clusters deposited in rare gas matrices [221], which has been interpreted as a manifestation of collective excitations (Mie plasmons) of the s electrons influenced by the ellipsoidal shape of the clusters. Some similarities but also some differences in the general trend with cluster size have been observed by comparing the optical absorption data shown in [221] with these EELS data [214]. In this context, it is important to note that EELS probes... 

We have analyzed the thermodynamic, magnetic and ultrasound attenuation data on oriented saaiples of the hlgh-T superconductors within the context of anisotropic Glnzburg-LSndau theory for coupled, even-parity superconducting states. We are able to present a consistent Interpretation of the data In terms of the coexistence of a quasi-two-dimensional d-wave state, with critical temperature T. - T and a more Isotropic mixed (s+d)-wave state with critical tempertaure T < T We predict the possibility of a "kink" in the temperature dependence of the lower critical field near 0 9T, which should be tested by experiments on single crystals. 

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