شاخص های غیرخطی به منظور بررسی تاثیر علمی مجله

The purpose of this study is to define a bibliometric indicator of the scientific impact of a journal, which combines objectivity with the ability to bridge many different bibliometric factors and in particular the side factors presented along with celebrated ISI impact factor. The particular goal is to determine a standard threshold value in which an independent self-organizing system will decide the correlation between this value and the impact factor of a journal. We name this factor “Cited Distance Factor (CDF)” and it is extracted via a well-fitted, recurrent Elman neural network. For a case study of this implementation we used a dataset of all journals of cell biology, ranking them according to the impact factor from the Web of Science Database and then comparing the rank according to the cited distance. For clarity reasons we also compare the cited distance factor with already known measures and especially with the recently introduced eigenfactor of the institute of scientific information (ISI).

Ever since the initial celebrated work by Garfield [13], Garfield and Merton [14], Pinski and Narin [33] on the evaluation of a scientific impact of a scientific journal, a great body of research has emerged on the application of information processing methods for evaluating scientific publication venues, extending it also to the evaluation of an individuals’ research output [20]. Nonetheless, the issue concerning the evaluation of a journals’ scientific impact still remains the essential priority of the scientometrics field [4], [37] and [22] due to the fact that is often used as a yardstick to provide an indication for the allocation of scientific budgets, the direction and future of research, as well as organizational decisions such as the employment of the researchers, the effectiveness of the research policy pursued and the subscription policy of academic libraries. The journal citation reports (JCR) provided by the Institute for Scientific Information (ISI), instituted by the work of Garfield [12] are often the main source for these indicators to academic and research evaluation committees. Undoubtedly, in current academic practice, JCR is one of the most used sources for facilitating a researcher’s access to high-quality, latter-day research.1 Apart from the impact factor, ISI provides a set of journal performance indicators supplied along with the impact factor of the journal. These performance indicators are categorized as follows: (a) Impact Factor (IF), a measure of the frequency with which the average article in a journal has been cited in a given period of time which is referred to, in a two year time span after publication in other words this cites in year x to items published in: x − 1 and x − 2; (b) Immediacy index (I.I) which concerns the average number of times an article is cited in the year it is published; (c) Cited half-life (Cd. H-L), the number of years, going back from the current year, that account for half the total citations received by the cited journal in the current year; (d) Citing half-life (Cg. H-L), the number of years from the current year that account for 50% of the cited references from articles published by a journal in the current year. 2

This study tackled the definition of a bibliometric indicator that concludes the IF with the side performance indicators of a scientific journals namely the Immediacy Index (II) , the Cited half life (Cd-hl) and the Citing half-life (Cg-hl). The goal was to create a factor that would correlate the four aforementioned factors that were previously rather uncorrelated. To comply with this objective, we used a well-fitted Elman neural network. The major issue that had to be addressed with this setting was in the ranking of the IF’s categories – max, med and min – which were the training groups of the neural network. For this reason we executed a multiple t-test trial, in order to create the training groups of vectors. Every vector had a (1 × 4) dimension. The next step was the test of the degree of the convergence’s convenience of learning procedure (see Fig. 3). The intuition of using the Elman neural network helped to create bounded limits, where under the testing procedure the ranking of the candidate vector moves within a predetermined range of values. In this way, we created a value called Cited Distance (CD) which emerges from the relative difference of the approximation value that the neural network attributed from the lower bounded limit (−1.5) as presented in Table 1. The journal’s ranking according to the IF was slightly differentiated using our method. The validity of the classification of the extracted CD factor in the three categories was controlled using t-test. In particular, we created the (3) three groups after bootstrapping experimentation. These were submitted in a t-test control which was presented in Table 2, Table 3 and Table 4. According to the results we concluded that the null hypothesis of non-homogeneity in all cases is to be rejected because these values are greater than the significant value 0.8. Taking this into account, we considered that the classification of these groups is correct. In addition, in an extra Cross-correlation control among different vectors, which have been chosen randomly (see Table 5), an extra corroboration of the Table 2, Table 3 and Table 4, for example, the vector 2 versus 68 has been observed, which gave a significant value, namely r = 0.10, showing the non-homogeneity relationship, while the vector 1 versus 2 yielded another significant value, namely r = 0.99, showing the homogeneity relationship. The differentiation test was performed using the non- parametric Wilcoxon method (see Table 6). and showed that the ranking according to the IF did not change dramatically using the CD According to Table 6 a bigger differentiation was noticed in category (P > 0.5974), whereas the differentiation was lower in the max (P > 0.9752) and intercalary in the min (P > 0.7297).The probability value was explicated as the satisfaction’s coefficient of the null hypothesis with (P = 1) in the case where the two groups were identical. The qualitative analysis of the results showed that all the vectors took part in the configuration (and they should) of the ranking. In Table 8, which is a part of Table 1, we can see that the differentiation occurred from cited half-life, citing half-time and immediacy index. As cited half-life, citing half-time and immediacy index are closer to zero, the order of the initial ranking increases (see Table 7, Table 8 and Table 9). The benchmarking analysis presented in Section 4.3 also concludes the merit of the CD factor as a complementary index for the evaluation of a scientific venue, in that case a scientific journal (see Table 10). Table 7. The ranking correlation between 155 journals selected via ISI biological recourse. Rank CD Rank IF Rank H index Rank eigenfactor CD Impact factor H index Eigenfactor Abbr. journal title 1 1 136 54 0.5155 31.921 157 .178 NAT REV MOL CELL BIO 2 3 120 116 0.5229 26.382 287 .235 NAT MED 3 4 121 120 0.5282 23.545 116 .052 ANNU REV CELL DEV BI 4 2 149 129 0.5284 29.887 408 .670 CELL 5 6 54 136 0.5327 17.148 82 .032 CELL METAB 6 5 86 143 0.5404 17.623 173 .187 NAT CELL BIOL 7 9 151 149 0.5655 13.444 168 .057 CURR OPIN CELL BIOL 8 8 66 150 0.5661 13.527 133 .070 TRENDS CELL BIOL 9 7 118 151 0.5744 14.795 253 .316 GENE DEV 10 10 39 39 0.5785 13.156 192 .309 MOL CELL 11 11 150 46 0.5875 12.436 106 .146 DEV CELL 12 12 116 80 0.6059 11.816 82 .023 CYTOKINE GROWTH F R 13 15 135 82 0.6299 10.15 112 .056 CURR OPIN STRUC BIOL 14 14 129 135 0.6342 10.15 116 .057 CURR OPIN GENET DEV 15 13 48 146 0.6404 11.085 60 .122 NAT STRUCT MOL BIOL 16 16 132 148 0.6965 9.653 160 .146 PLANT CELL 17 19 143 66 0.7588 8.254 93 .057 CELL DEATH DIFFER 18 20 57 104 0.7912 7.531 76 .037 STEM CELLS 19 21 59 124 0.7915 7.45 79 .071 EMBO REP 20 17 82 130 0.7923 9.598 214 .272 J CELL BIOL 21 22 115 131 0.7943 7.244 64 .029 TRENDS MOL MED 22 18 134 132 0.8447 8.662 247 .342 EMBO J 23 24 142 134 0.9091 6.533 64 .039 TRAFFIC 24 25 32 137 0.9091 6.482 61 .022 SEMIN CELL DEV BIOL 25 29 63 141 0.9234 6.365 34 .007 AGEING RES REV 26 23 81 142 0.9526 6.791 150 .130 FASEB J 27 26 72 145 0.9588 6.44 172 .269 ONCOGENE 28 28 105 147 0.9713 6.383 137 .193 J CELL SCI 29 31 130 155 0.9886 5.854 36 .012 AGING CELL 30 30 155 81 10.166 6.028 125 .177 MOL BIOL CELL 31 27 123 92 10.379 6.42 206 .369 MOL CELL BIOL 32 37 137 105 10.654 4.657 21 .005 AUTOPHAGY 33 33 146 110 10.749 5.293 52 .028 CELL MICROBIOL 34 35 61 118 10.910 5.239 94 .060 CELL MOL LIFE SCI 35 34 124 123 12.001 5.246 77 .031 J MOL CELL CARDIOL 36 40 102 152 12.052 4.409 60 .026 TISSUE ENG 37 47 109 63 12.131 4.217 33 .013 CELL RES 38 43 80 69 12.147 4.317 36 .017 MOL CANCER RES 39 48 148 102 12.175 4.17 13 .001 CELL ONCOL 40 36 95 115 12.180 5.231 90 .060 STRUCTURE 41 41 126 121 12.524 4.374 70 .035 BBA-MOL CELL RES 42 45 131 128 12.667 4.288 30 .010 PIGM CELL RES 43 42 145 140 13.188 4.338 58 .018 CELL CALCIUM 44 49 42 144 13.194 4.147 74 .031 CELL SIGNAL 45 44 79 153 13.348 4.308 53 .018 MECH AGEING DEV 46 53 91 32 13.384 3.871 46 .001 CELL TRANSPLANT 47 38 98 48 13.439 4.608 91 .034 AM J RESP CELL MOL 48 64 50 60 13.439 3.553 18 .005 CYTOTHERAPY 49 51 55 91 13.526 4.009 88 .035 INT J BIOCHEM CELL B 50 68 60 93 13.632 3.314 31 .045 CELL CYCLE 51 32 69 95 13.800 5.506 33 .012 INT REV CYTOL 52 54 104 101 13.915 3.87 42 .007 MOL MEMBR BIOL 53 50 128 109 13.927 4.128 95 .050 J LEUKOCYTE BIOL 54 138 144 111 13.991 1.157 9 .000 IEE P SYST BIOL 55 66 101 138 14.001 3.493 31 .021 PHYSIOL GENOMICS 56 63 37 139 14.263 3.557 34 .006 CELL PHYSIOL BIOCHEM 57 56 51 56 14.357 3.752 19 .011 BIOL CELL 58 46 92 107 14.468 4.23 95 .057 AM J PHYSIOL-CELL PH 59 75 25 113 14.713 3.092 19 .007 BMC CELL BIOL 60 57 56 114 14.759 3.742 31 .005 GROWTH FACTORS 61 79 140 126 15.015 2.978 26 .008 CYTOM PART A 62 67 141 25 15.220 3.381 77 .272 J CELL BIOCHEM 63 72 147 52 15.284 3.209 21 .004 MITOCHONDRION 64 61 93 59 15.344 3.654 58 .033 PLANT CELL PHYSIOL 65 76 153 84 15.385 3.043 45 .015 APOPTOSIS 66 131 29 89 15.484 1.447 12 .002 CELL COMMUN ADHES 67 65 38 94 15.509 3.539 77 .020 BBA-MOL CELL BIOL L 68 69 138 96 15.534 3.299 67 .022 GENES CELLS 69 73 94 100 15.575 3.12 31 .004 CELL PROLIFERAT 70 62 110 127 15.748 3.643 87 .041 J CELL PHYSIOL 71 60 114 61 15.878 3.677 69 .027 J STRUCT BIOL 72 59 152 98 15.881 3.687 24 .10 MATRIX BIOL 73 77 108 108 16.006 3.033 48 .009 IMMUNOL CELL BIOL 74 78 139 133 16.112 2.989 65 .032 FRONT BIOSCI 75 71 154 73 16.272 3.224 52 .012 EUR J CELL BIOL 76 58 89 106 16.362 3.695 107 .065 EXP CELL RES 77 85 52 117 16.400 2.857 42 .010 IUBMB LIFE 78 55 77 42 16.467 3.791 58 .015 HISTOPATHOLOGY 79 97 113 77 16.763 2.402 30 .021 CYTOGENET GENOME RES 80 39 100 87 16.860 4.571 28 .001 PROG HISTOCHEM CYTO 81 100 65 97 17.024 2.308 21 .003 NEUROSIGNALS 82 81 106 99 17.146 2.94 20 .001 ANAL QUANT CYTOL 83 84 107 57 17.291 2.893 49 .011 HISTOCHEM CELL BIOL 84 86 46 83 17.361 2.853 46 .007 CELL STRESS CHAPERON 85 70 84 90 17.566 3.263 145 .171 FEBS LETT 86 129 117 122 17.582 1.493 11 .037 STEM CELL REV 87 83 73 29 17.620 2.899 49 .010 DIFFERENTIATION 88 80 103 51 17.642 2.971 66 .026 MOL CELL ENDOCRINOL 89 82 83 75 17.719 2.9 41 .007 NITRIC OXIDE-BIOL CH 90 96 87 103 18.216 2.419 88 .011 BIOCHEM CELL BIOL 91 109 133 37 18.257 1.953 30 .005 CELL BIOCHEM BIOPHYS 92 74 33 112 18.311 3.115 33 .003 BIOSCIENCE REP 93 98 75 65 18.373 2.364 35 .005 MOL CELL PROBE 94 95 97 78 18.403 2.445 37 .007 WOUND REPAIR REGEN 95 110 45 38 18.470 1.935 29 .005 J NEUROCYTOL 96 88 96 43 18.568 2.634 54 .007 J BIOENERG BIOMEMBR 97 87 112 45 18.689 2.667 52 .010 J INTERF CYTOK RES 98 111 43 154 18.703 1.916 30 .008 MOL CELLS 99 101 64 67 19.001 2.245 61 .010 TISSUE ANTIGENS 100 94 78 119 19.132 2.483 44 .007 CELL MOL NEUROBIOL 101 119 122 55 19.214 1.776 32 .005 CELLS TISSUES ORGANS 102 112 15 79 19.226 1.915 27 .004 PLATELETS 103 102 36 24 19.275 2.169 48 .012 CYTOKINE 104 117 24 68 19.341 1.815 31 .002 J RECEPT SIG TRANSD 105 121 99 12 19.414 1.74 24 .003 ENDOTHELIUM-J ENDOTH 106 106 125 125 19.471 2.007 45 .009 HISTOL HISTOPATHOL 107 107 21 36 19.509 2 45 .006 PROSTAG LEUKOTR ESS 108 104 23 88 19.520 2.068 40 .008 DEV GENES EVOL 109 116 74 71 19.547 1.831 27 .005 GROWTH HORM IGF RES 110 105 88 33 19.690 2.064 37 .003 EUR CYTOKINE NETW 111 103 68 21 19.772 2.078 67 .005 MOL MED 112 92 111 35 19.880 2.538 57 .014 MOL REPROD DEV 113 115 119 44 19.919 1.861 43 .006 DNA CELL BIOL 114 108 71 5 20.190 1.968 38 .006 PROSTAG OTH LIPID M 115 124 41 74 20.223 1.676 20 .004 CELL MOL BIOL LETT 116 155 44 64 20.342 0 15 .000 CELL STEM CELL 117 91 18 47 20.376 2.542 47 .009 CELL MOTIL CYTOSKEL 118 140 35 41 20.562 1.13 12 .003 J MOL HISTOL 119 89 62 49 20.686 2.613 67 .020 CELL TISSUE RES 120 154 67 18 20.860 0 4 .000 IET SYST BIOL 121 114 19 86 21.031 1.882 4 .004 CELL STRUCT FUNCT 122 93 127 23 21.092 2.527 58 .011 J MEMBRANE BIOL 123 125 5 70 21.123 1.561 25 .003 CELL BIOCHEM FUNCT 124 127 12 50 21.161 1.547 26 .002 PATHOBIOLOGY 125 123 70 53 21.237 1.707 61 .023 MOL CELL BIOCHEM 126 128 49 3 21.319 1.504 29 .006 INFLAMM RES 127 126 90 13 21.378 1.547 80 .007 CELL BIOL INT 128 113 40 7 21.407 1.908 31 .004 DEV GROWTH DIFFER 129 90 47 14 21.642 2.6 17 .000 ADV ANAT EMBRYOL CEL 130 137 17 17 21.651 1.162 24 .002 MEDIAT INFLAMM 131 120 34 58 21.668 1.758 29 .002 CELL BIOL TOXICOL 132 134 53 34 21.934 1.261 18 .002 EUR J HISTOCHEM 133 118 58 40 22.118 1.808 49 .008 CELL IMMUNOL 134 136 11 76 22.266 1.222 20 .002 CYTOPATHOLOGY 135 145 76 8 22.485 0.886 16 .001 FOLIA HISTOCHEM CYTO 136 153 13 19 22.513 0.214 3 .000 BRAIN CELL BIOL 137 132 3 72 22.659 1.443 25 .002 ZYGOTE 138 122 14 15 22.670 1.731 36 .005 J MUSCLE RES CELL M 139 139 30 26 22.787 1.154 40 .005 CELL MOL BIOL 140 130 8 11 23.111 1.493 34 .004 PROTOPLASMA 141 149 28 16 23.659 0.548 34 .002 IN VITRO CELL DEV-PL 142 144 85 85 23.840 0.938 20 .002 ACTA HISTOCHEM 143 133 26 30 24.455 1.286 18 .000 BIOTECH HISTOCHEM 144 141 1 1 24.496 1.085 31 .004 CONNECT TISSUE RES 145 135 16 6 24.525 1.237 29 .002 TISSUE CELL 146 148 7 28 24.551 0.589 25 .001 CYTOTECHNOLOGY 147 147 27 2 24.830 0.66 34 .002 IN VITRO CELL DEV-AN 148 142 6 27 24.881 1 28 .001 INFLAMMATION 149 152 10 20 25.014 0.266 5 .000 BIOL MEMBRANY 150 150 31 62 25.090 0.456 13 .000 ACTA HISTOCHEM CYTOC 151 151 20 10 25.158 0.333 11 .000 BIOCELL 152 146 22 9 25.267 0.697 38 .003 ACTA CYTOL 153 155 9 22 25.573 0 35 .004 METHOD CELL BIOL 154 99 2 31 25.660 2.335 40 .018 J HISTOCHEM CYTOCHEM 155 143 4 4 26.713 0.986 24 .002 ARCH HISTOL CYTOL Table options Table 8. Changes in order in terms of cited half-life. Rank CD Rank IF Abbreviated journal title Impact factor Immediacy index Cited half-life Citing half-time 2 3 NAT MED 26.382 6.342 5.7 4.5 4 2 CELL 29.887 6.402 8.7 4.5 Table options Table 9. Changes in order in terms of citing half-time. Rank CD Rank IF Abbreviated journal title Impact factor Immediacy index Cited half-life Citing half-time 144 141 CONNECT TISSUE RES 1.085 0.098 10 8.3 145 135 TISSUE CELL 1.237 0.073 10 10 Table options Table 10. Changes in order in terms of immediacy index. Rank CD Rank IF Abbreviated journal title Impact factor Immediacy index Cited half-life Citing half-time 23 24 TRAFFIC 6.533 0.98 3.7 5.9 25 29 AGEING RES REV 6.365 0.5 3.6 6 Table options To this end the contributions of this study can be summarized in the three following points: 1. We introduced a new standard measure (threshold −1.5) for the evaluation of each journal, which has taken us towards the direction of using indirect comparison for the journals. 2. We created a global factor called CD which includes the four (4) most significant factors, which, according to evaluated results, is considered to be sounder than those of IF. 3. We introduced three new homogeneous categories (max, med, min) for evaluation the journals. Their statistical evaluation showed that these may be validly used for the characterization of each journal.