Reliability, of data

Check the toxicity of process materials, identify short and long term effects for various modes of entry into the body and different exposure tolerance Identify the relationship between odour and toxicity for all process materials Determine the means for industrial hygiene recognition, evaluation and control Determine relevant physical properties of process materials under all process conditions, check source and reliability of data... 

The in vitro bioassay for dioxins with cleaned sediment extracts (DR-CALUX) proved to comply with the QA/QC criteria needed to guarantee the reliability of data in an inter- and intralaboratory study (Besselink et al., 2004). The chemical stability of dioxins makes it possible to apply destructive clean-up procedures which remove all matrix factors. Sample extraction and cleanup for other in vitro bioassays for specific mechanisms of toxicity require further development to make sure that the chemicals of interest are not lost or unwanted chemicals included in the sediment extract to be tested. Table 4 summarizes possible bioassays that could be performed in addition to chemical analyses with the dredged sediment in a licensing system. 

In more than one respect, the small-amplitude sinuosoidal a.c. method can be superior to the large-amplitude step methods for the study of coupled homogeneous reactions. First, the wide range of frequencies at which meaningful data can be obtained will correspond to an equally wide range of rate constants on which, in principle, information can be obtained. Second, the a.c. perturbation can be superimposed on a large-amplitude d.c. or step perturbation so that information in the time scale of the latter is incorporated as well. Moreover, this affords an internal check on the reliability of data interpretations. Finally, it is important... 

Over the last 20 years the reliability of data produced by analytical laboratories has increased dramatically. Strict requirements have ensured that the data were produced under defined standards of quality with a stated level of confidence. The routine day-to-day activities (e.g., matrix fortifications) to control, assess, and ensure the quality of generated data are the quality controls associated with analytical processes. The management of the system that ensures that these processes are in place and functional is the quality assurance portion of the laboratory program to produce reliable data. 

No data on genotype and reliability of data on phenotype questionable because of lack of strain authentication Single stock experiments done... 

An important feature of the traceability structure described above is an improved reliability of data as a result of reference measurements rather than the use of reference materials alone. Reference measurements allow exact matching of the sample matrix. This is very important in clinical chemistry where difficult matrices are quite common. 

The analytical methodology must meet realistic expectations regarding sensitivity, accuracy, reliability, precision, interferences, matrix effects, limitations, cost, and the time required for analysis (Keith et al., 1983). Selection of the optimum analytical method is one of the most important factors influencing the reliability of data (Keith, 1980, 1991 ACS, 1983). 

Detection -reliability of data gathered by observers (Brown Van der... 

The opinions issued by SCHER are basically scientific peer reviews, similar to a longer referee report for a piece submitted to a scientific journal. Just like any peer reviewer would do, SCHER comments on the data used in risk assessments, especially on the lack or reliability of data as well as on methods, approaches and interpretations. Uncertainty of exposure and effects and factors conditioning uncertainty are discussed, often resulting in statements such as firm conclusions cannot be reached . 

A list of k2/ki values is available in Section 2.IV.4 of Ref. but, as has been pointed out, the reliability of data cannot be guaranteed. Nevertheless, one can conclude that for aliphatic amines q = k /k = 0.3-0.5 (no or weakly negative substitution effect) and for aromatic amines with the exception of phenylenediamines Q = 0.17-0.25. 

Calculations, interfaces,. .. tested access rights defined and limited, if applicable backup/restore procedure available training of technical staff and users Accuracy and reliability of data ensured... 

Preparation of consistent tabulations of thermod3maniic data is a difficult task because of the complex interrelations of the data. One new set of data can require changes in numerous related values. For inorganic thermodynamic compilations, the logical starting point is a reliable tabulation of data for the elements. If data for compounds are to be compared, they must be based on the same elemental data. Once the thermod3mamic data for the elements have been fixed, then equilibria involving the elements and compounds can be treated to fix the stabihty of the compounds. When the heats of subhmation and ionization of the elements are available, Bom-Haber cycle calculations can be carried out for ionic compounds to check the reliability of data for the compounds. 

Determination of Cd, Pb and U were performed by magnetic sector high resolution ICP-MS. The lack of CRMs in a snow matrix did not allow for a direct check of the measurement accuracy, but reasonable confidence in the reliability of data was reached through the use of other analytical techniques, i.e., ETA AAS and DP-ASV. Mean concentrations were found to be (pg g ) 0.39 for Cd, 5.0 for Pb and 0.04 for U. 

Out-of-laboratory measurements are undertaken across a broad range of industrial and analytical sectors for a variety of reasons in clinical and medical diagnostics for the control of chemical and petrochemical production processes and to monitor emissions and discharges to the environment. The validity of data derived from such measurements is clearly of vital importance, for example to demonstrate compliance with environmental legislation. However, it is particularly difficult to obtain valid and reliable measurements outside the laboratory. The inability to control the environment in which the measurements are made and the use of untrained operators both have potential to impact significantly on the reliability of data. The situation is made worse because of the lack of adequate QA and QC procedures, the shortage of reference materials and calibration standards, and... 

Unfortunately, there is no simple and widely applicable method for determining the reliability of data with absolute certainty. Often, estimating the quality of experimented results reejuires as much effort as collecting the data. Reliability can be assessed in several wa vs. Experiments designed to reveal the presence of errors can be peiformed. Standards of known composition can be analyzed and the results compared with the known composition. A few minutes in the library to consult the chemical literature can be profitable. Calibrating equipment usually enhances the quality of data. Finally, statistical tests can be applied to the data. Because none of these options is perfect, we must ultimately make judgments as to the probable accuracy of our results. These judgments tend to become harsher and less optimistic with experience. The quality assurance of analytical methods and the ways to validate and report results are further discussed in Section 8D-3. 

FIGURE 2 Unified elements that ensure reliability of data from analytical methodology. 

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