SCORE description

Flavor Score Description Range of Optical Density (532 mu)... 

PCR is a combination of PCA and MLR, which are described in Sections 9.4.4 and 9.4.3 respectively. First, a principal component analysis is carried out which yields a loading matrix P and a scores matrix T as described in Section 9.4.4. For the ensuing MLR only PCA scores are used for modeling Y The PCA scores are inherently imcorrelated, so they can be employed directly for MLR. A more detailed description of PCR is given in Ref. [5. ... 

Thus, an orbital description of the motion of an electron contains the same information conveyed by the holes made by darts in a dartboard. After the board has been used in many games, the distribution of holes shows how successful earlier players had been in their scoring. There are many holes near the bullseye and, moving away from it, there is a regular decrease in the number of holes per square centimeter of dartboard. At any given distance from the bullseye, the density of dart holes (number per square centimeter) is a measure of the probability that the next throw will (and there. 

In the results the emissions of mercury appear to have a very substantial contribution for the human toxicity impact score. These emissions are caused by the coproduction of chlorine and sodium hydroxide by electrolysis using a mercury cell. However, this technique is phased out. Therefore, the process descriptions in the Ecoinvent database do not represent up to date technology. In the Ecoinvent database the process for PVC production, in which chlorine is used as one of the compounds, is an aggregated processes based on, seemingly outdated, data from PlasticsEurope. These outdated data also influence the impacts related to waste treatment by incineration because sodium hydroxide is necessary for the waste incineration process. 

Postmortem Procedures. Rabbits are euthanized by lethal dose of a barbiturate soon after the last vaginal irritation scores are collected. The vagina is opened by longitudinal section and examined for evidence of mucosal damage such as erosion, localized hemorrhage, and so on. No other tissues are examined. No tissues are collected. After the macroscopic description of the vagina is recorded, the animal is discarded. 

Conners Parent-Teacher Questionnaire. See descriptions above for Conners Parent Questionnaire and below for the Conners Teacher Questionnaire (TQ). The PTQ is used in conjunction with either the PQ to TQ and yields a total score only (i.e., no subscales are given). The PTQ takes about five minutes to complete and is not used pretreatment. 

Figure 6. Female reaction to a command Turning-around movements. Sequence (a) shows the digitized pictures for a reaction to a command. The female command giver is standing at the camera. On the command Please turn around the female turns around. On the left side of each picture the stimulus male can be seen. Sequence (b) shows the difference pictures with the regions for the stimulus and the subject which are used to calculate the mean grey density. In (c) these grey density levels are presented as z-scores. The movement has three phases phase I where an initiation movement is made. Phase II where the actual turn around movement happens and phase III where an additional movement is added to the turn around (see also text). The description parameters for the movment are the same as in Fig.4c. The difference to Figure 4 is that the threshold is calculated dynamically for each 10 frames in order to deal with shifts of grey density changes.

The goal of Q-mode FA is to determine the absolute abundance of the dominant components (i.e., physical or chemical properties) for environmental contaminants. It provides a description of the multivariate data set in terms of a few end members (associations or factors, usually orthogonal) that account for the variance within the data set. A factor score represents the importance of each variable in each end member. The set of scores for all factors makes up the factor score matrix. The importance of each variable in each end member is represented by a factor score, which is a unit vector in n (number of variables) dimensional space, with each element having a value between -1 and 1 and the... 

While the results of the work performed by Vaidyanathan et al.44 are scientifically useful, the thorough treatment the authors give to chemometrics is excellent. There is a detailed description of principal components (PCA) with a number of pictures of loadings to help explain the process. Using PC scores, three-dimensional representations of the samples are shown. This is a good paper for someone just beginning to use chemometrics. 

Finally, we examine descriptive statistics that relate attribute-level performance scores and share of customer wallet. Although in general we find a positive correlation between attribute performance scores and share of customer wallet, case-by-case examination reveals exceptions. 

Scores are good for quantitative analysis, but don t adequately eonvey a picture of qualitative changes in behavior. And commanders in the field wanted that picture, in order to get a better feef for tiie effects of BZ and other drugs. They needed some verbal descriptions and videotape. We therefore expanded our protocol, including half a dozen additional ways to document the volunteer responses, trying to keep them in a form understandable to non-pharmacologists ... 

Plot Species Tree Density, 1973 Avera Injury Score Mortality Rate, % Accumulated Mortality, % Injury 1974 Description ... 

Figure 8.6 Contraceptive contained in the original package, demonstrating high-throughput classification possibilities. (A) Visible image (B) description of sample positioning and (C) NIR PCA score image showing contrast between the placebo and the active-containing tablets.

Identification and description of biocide fields of use and the estimation of scores based on the level of human and environmental exposure, Haskoning 1999. 

To test the potential of PLS to predict odour quality, it was used in a QSAR study of volatile phenols. A group of trained sensory panelists used descriptive analysis (28) to provide odour profiles for 17 phenols. The vocabulary consisted of 44 descriptive terms, and a scale fiom 0 (absent) to S (very strong) was used. The panel average sensory scores for the term sweet were extracted and used as the Y-block of data, to be predicted from physico-chemical data. 

The SIMCA method has been developed to overcome some of these limitations. The SIMCA model consists of a collection of PCA models with one for each class in the dataset. This is shown graphically in Figure 10. The four graphs show one model for each excipient. Note that these score plots have their origin at the center of the dataset, and the blue dashed line marks the 95% confidence limit calculated based upon the variability of the data. To use the SIMCA method, a PCA model is built for each class. These class models are built to optimize the description of a particular excipient. Thus, each model contains all the usual parts of a PCA model mean vector, scaling information, data preprocessing, etc., and they can have a different number of PCs, i.e., the number of PCs should be appropriate for the class dataset. In other words, each model is a fully independent PCA model. 

X A) is related to the calibration samples and is termed the matrix of scores and E (/ x J) is the part of the data that is not modelled by the A factors. As mentioned above, A is the number of latent variables that are retained in the model. The loadings in P define a new coordinate system (a rotation of the original axis of the measured variables) and the scores T are the coordinates of the samples in this new coordinate system (see Figure 3.4 for a brief description). 

---