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Table 4: Results of using AND/OR/INV blocks. Numbers in parentheses include close to correct solutions. Question Non-expert Students

in A Logic Block Enabling Logic Configuration by Non-Experts in Sensor Networks
by Susan Cotterell, Frank Vahid 2005
"... In PAGE 3: ... Users instantiated and connected the blocks. Table4 summarizes results. We see the AND/OR/NOT blocks are competitive with the best truth table and logic sentences.... ..."
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Table 1. Rate of agreement for non{experts compared to experts

in Prosodic Transcription Of Glasgow English: An Evaluation Study Of Glatobi
by Catherine Mayo, Matthew Aylett, D. Robert Ladd
"... In PAGE 3: ....4. Non{experts compared to experts The use of non{expert as well as expert GlaToBI transcribers was critical in order to assess the ease and accuracy with which the new system could be learnt. As shown in Table1 , the level of agreement among the non{experts (N{E) was generally equal to or only slightly lower than among the experts (E), indicating that with the appropriate training, GlaToBI can be used by non{expert transcribers to... ..."

Table 7a. Inter-rater reliability of composite rating Rk(f) based on 10 non-experts.

in Focal Accent -- f_0 Movements and Beyond
by Heldner Mattias 2001
"... In PAGE 49: ....3.1. Reliability indices Table7 a shows the inter-rater reliability coefficients of the composite rating, Rk(f), and Table 7b the average reliability of a single transcriber, R 1(f), for boundaries and prominences in the read and spontaneous speech using the same procedures as described for the expert transcribers (see 3.... In PAGE 49: ....3.1. Reliability indices Table 7a shows the inter-rater reliability coefficients of the composite rating, Rk(f), and Table7 b the average reliability of a single transcriber, R 1(f), for boundaries and prominences in the read and spontaneous speech using the same procedures as described for the expert transcribers (see 3.... In PAGE 49: ... Table7 b. Inter-rater reliability of single rater R1(f) based on 10 non-experts.... ..."

Table 7a. Inter-rater reliability of composite rating Rk(f) based on 10 non-experts.

in Labelling of Boundaries and Prominences By Phonetically Experienced and Non-Experienced Transcribers
by Eva Strangert, Mattias Heldner
"... In PAGE 17: ...3.1 Reliability indices Table7 a shows the inter-rater reliability coefficients of the composite rating, Rk(f), and Table 7b the average reliability of a single transcriber, R 1(f), for boundaries and prominences in the read and spontaneous speech using the same procedures as described for the expert transcribers (see 3.... In PAGE 17: ...3.1 Reliability indices Table 7a shows the inter-rater reliability coefficients of the composite rating, Rk(f), and Table7 b the average reliability of a single transcriber, R 1(f), for boundaries and prominences in the read and spontaneous speech using the same procedures as described for the expert transcribers (see 3.... In PAGE 17: ... Table7 b. Inter-rater reliability of single rater R1(f) based on 10 non-experts.... ..."

Table 7b. Inter-rater reliability of single rater R1(f) based on 10 non-experts.

in Labelling of Boundaries and Prominences By Phonetically Experienced and Non-Experienced Transcribers
by Eva Strangert, Mattias Heldner
"... In PAGE 17: ...3.1 Reliability indices Table7 a shows the inter-rater reliability coefficients of the composite rating, Rk(f), and Table 7b the average reliability of a single transcriber, R 1(f), for boundaries and prominences in the read and spontaneous speech using the same procedures as described for the expert transcribers (see 3.... In PAGE 17: ...3.1 Reliability indices Table 7a shows the inter-rater reliability coefficients of the composite rating, Rk(f), and Table7 b the average reliability of a single transcriber, R 1(f), for boundaries and prominences in the read and spontaneous speech using the same procedures as described for the expert transcribers (see 3.... In PAGE 17: ...or the expert transcribers (see 3.3.2). Table7 a. Inter-rater reliability of composite rating Rk(f) based on 10 non-experts.... ..."

Table 1: Training set accuracy for just the Greebles. Fig- ures in parentheses denote standard error. Expert task Greebles training set accuracy(%) Non-expert 71.2 (2.00)

in Visual Expertise is a General Skill
by Maki Sugimoto, Garrison W. Cottrell 2001
"... In PAGE 4: ...were slower than the book experts (t(38) = 3:08; p lt; 0:005), and the book experts were slower than the cup experts (t(38) = 3:22; p lt; 0:005). Table1 shows that despite the overall RMSE having been controlled, the Non-experts were still non-experts at Greebles after training on them. Further training on the Non-experts would have widened the gap between train- ing times on the Greebles for Experts and Non-experts even more.... ..."
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Table 1: Training set accuracy for just the Greebles. Fig- ures in parentheses denote standard error. Expert task Greebles training set accuracy(%) Non-expert 71.2 (2.00)

in Visual expertise is a general skill
by Maki Sugimoto 2001
"... In PAGE 4: ...were slower than the book experts (t#2838#29=3:08; p #3C 0:005), and the book experts were slower than the cup experts (t#2838#29=3:22; p #3C 0:005). Table1 shows that despite the overall RMSE having been controlled, the Non-expertswere still non-expertsat Greebles after training on them. Further training on the Non-experts would have widened the gap between train- ing times on the Greebles for Experts and Non-experts even more.... ..."
Cited by 3

Table 5. Non-expert and expert mental models. P ( ) is the probability that the non-expert

in Risk Communication in Security Using Mental Models
by Debin Liu, Farzaneh Asgharpour, L. Jean Camp
"... In PAGE 4: ... Based on these tables, we find the expert and non-expert mental models indicated in the Appendix A - Table 5. DNE E As one can see in Table5 , some of the probabilities are very low. The reason is that in average 34.... ..."

Table 1. Difference and intra- and interobserver variability for the manual and semi-automatic segmentation method, both volume and overlap are compared (the difference man-semiauto is averaged over the absolute value) Manual Segmentation Semi-automatic segmentation

in Interactive multi-scale watershed segmentation of tumors in MR brain images
by Marloes Mj Letteboer A, Wiro J Niessen A, Peter Wa Willems B, Erik B Dam C, Max A Viergever A
"... In PAGE 5: ...rise. The average overlap, calculated with the similarity measure, is 88.9 g177 6.2 %. Because of the wide range in difference between the two methods the results are listed for every tumor separately in Table1 , as well as the inter- and intraobserver variabilities. As said before, one clinical expert and one non-expert performed the manual segmentation.... ..."

Table 3: Number of interactions and time used.

in Evaluating Multi-modal Input Modes in a Wizard-of-Oz Study for the Domain of Web Search
by Ra Klein, Ingrid Schwank, Michel Généreux, Harald Trost, Alexandra Klein 2001
"... In PAGE 7: ... Generally, task completion times were longer if the test persons only used written input (cf. Table3 ). Expert users improved less by the use of spoken language than non-experts users did.... ..."
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