Identifying Scientific and Technical “Unicorns”

doi:10.2478/jdis-2021-0002

Abstract

Abstract:

Purpose: Using the metaphor of “unicorn,” we identify the scientific papers and technical patents characterized by the informetric feature of very high citations in the first ten years after publishing, which may provide a new pattern to understand very high impact works in science and technology.
Design/methodology/approach: When we set C_T as the total citations of papers or patents in the first ten years after publication, with C_T≥ 5,000 for scientific “unicorn” and C_T≥ 500 for technical “unicorn,” we have an absolute standard for identifying scientific and technical “unicorn” publications.
Findings: We identify 165 scientific “unicorns” in 14,301,875 WoS papers and 224 technical “unicorns” in 13,728,950 DII patents during 2001-2012. About 50% of “unicorns” belong to biomedicine, in which selected cases are individually discussed. The rare “unicorns” increase following linear model, the fitting data show 95% confidence with the RMSE of scientific “unicorn” is 0.2127 while the RMSE of technical “unicorn” is 0.0923.
Research limitations: A “unicorn” is a pure quantitative consideration without concerning its quality, and “potential unicorns” as C_T≤5,000 for papers and C_T≤500 for patents are left in future studies.
Practical implications: Scientific and technical “unicorns” provide a new pattern to understand high-impact works in science and technology. The “unicorn” pattern supplies a concise approach to identify very high-impact scientific papers and technical patents.
Originality/value: The “unicorn” pattern supplies a concise approach to identify very high impact scientific papers and technical patents.

Key words: Unicorn, Scientific paper, Technical patent, Citation analysis, Patent analysis

L. Xu, Lucy, Miao Qi, and Fred Y. Ye. "Identifying Scientific and Technical “Unicorns”." Journal of Data and Information Science, vol.6, no.2, 2021, pp.96-115. DOI: 10.2478/jdis-2021-0002

Figures/Tables 9

Figure 1.

Table 1

Table 2

Table 3

Table 4

Table 5

A selected top 10 technical patents of biomedical “unicorns” (2001-2010).

Code	Title	Inventor(s)	Patent No.	CT
Pn1	Producing humanized immunoglobulin, involves producing a cell containing DNA segments encoding humanized heavy and light chain variable regions, and expressing the DNA segments in the cell	QUEEN C L; SELICK H E	US6180370-B1; 2001	542
Pn2	Analyte level monitoring device for diabetes treatment, has transmitter arranged on substrate of electrochemical sensor, for transmitting signal indicating analyte level in bodily fluid	HELLER A; DRUCKER S M; JIN R Y; FUNDERBURK J V; et al.	WO200258537-A2; US2003100821-A1; US6560471-B1; 2002	514
Pn3	Spinal cord stimulation system includes surgical components, which consist of insertion needle and tunneling tools to aid implantation of electrode array and lead extension	MEADOWS P; MANN C M; PETERSON D K; et al.	US6516227-B1; 2003	674
Pn4	Surgical stapling instrument for laparoscopic and endoscopic clinical procedure has firing device that has a distally presented cutting edge longitudinally received between the elongated channel and the anvil	SHELTON IV F E; SETSER M E; HEMMELGARN B J; et al.	EP1479349-A1; US2004232196-A1; CA2467795-A1; 2004	514
Pn5	Surgical instrument for endoscopically inserting end effector, e.g. endo-cutter, grasper, cutter, and staplers, includes articulation control comprising actuator, and motion conversion mechanism	WALES K S	US2005006430-A1; CA2473482-A1; JP2005028148-A; 2005	717
Pn6	Surgical instrument e.g. endo-cutter for use during fastening of buttress pads to tissue, comprises staple applying assembly attached to elongate shaft, which includes opposing tissue compression surfaces	SHELTON F E; SHELTON F; WALES K S; et al.	EP1621141-A2; JP2006043451-A; US2006025816-A1; 2006	722
Pn7	Medical device e.g. surgical stapler, for e.g. stapling tissue, has articulation joint actuator to hold passive joint and end effector in fixed articulation state during unactuated state and to release joint during actuated state	SMITH K W; PALMER M A; KLINE K R; et al.	US2007187453-A1; US7404508-B2; AU2015201382-B2; 2007	817
Pn8	Surgical stapling apparatus includes drive assembly that is supported in the tool assembly and which has a knife blade disposed in an elongated longitudinal slot formed by the anvil plate and the staple cartridge	TARINELLI D; ARANYI E; SIMPSON R; et al.	WO2008109125-A1; US2009134200-A1; AU2008223389-A1; 2008	674
Pn9	Disposable loading unit for endoscopic surgical stapling instrument for incising fastened tissue, has anvil portion that is provided with staple-deforming cavity, and cover plate is secured for supporting anvil portion	ARMSTRONG G A; BLAIR G B; BRUEWER D B; et al.	EP2090235-A2; US2009206140-A1; CN101507634-A; 2009	571
Pn10	Motor e.g. stepper motor, driven surgical cutting and fastening instrument i.e. endoscopic instrument, for use by e.g. physician for endoscopic application, has motor with operational modes for portions of cutting stroke cycle of instrument	LAURENT R J; SHELTON F E; SMITH B W; et al.	EP2165664-A2; JP2010075694-A; US2010076474-A1; 2010	675

Table 5

Figure 2.

Table 6

Table 7

References 79

[1]	Ahmadpoor, M., & Jones, B.F. (2017). The dual frontier: Patented inventions and prior scientific advance. Science, 357(6351), 583-587. doi: 10.1126/science.aam9527 pmid: 28798128
[2]	Akune, Y., Lin, C.H., Abrahams, J.L., Zhang, J.Y., Packer, N.H., Aoki-Kinoshita, K.F., & Campbella, M.P. (2016). Comprehensive analysis of the N-glycan biosynthetic pathway using bioinformatics to generate UniCorn: A theoretical N-glycan structure database. Carbohydrate Research, 431, 56-63. doi: 10.1016/j.carres.2016.05.012 pmid: 27318307
[3]	Bartel, D.P. (2004). MicroRNAs: Genomics, biogenesis, mechanism, and function. Cell, 116(2), 281-297. doi: 10.1016/s0092-8674(04)00045-5 pmid: 14744438
[4]	Bertoli-Barsotti, L., & Tommaso, L. (2019). How mean rank and mean size may determine the generalised Lorenz curve: With application to citation analysis. Journal of Informetrics, 13(1), 387-396.
[5]	Bonaccorsi, A. (2007). Explaining poor performance of European science: Institutions versus policies, Science and Public Policy, 34, 303-316.
[6]	Bornmann, L., & Daniel, H.D. (2006). Selecting scientific excellence through committee peer review—A citation analysis of publications previously published to approval or rejection of post-doctoral research fellowship applicants. Scientometrics, 68(3), 427-440.
[7]	Bornmann, L., & Daniel, H. (2008). What do citation counts measure? A review of studies on citing behavior. Journal of Documentation, 64, 45-80.
[8]	Bornmann, L., & Marx, W. (2014). How to evaluate individual researchers working in the natural and life sciences meaningfully? A proposal of methods based on percentiles of citations. Scientometrics, 98(1), 487-509.
[9]	Bornmann, L., & Mutz, R. (2015). Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references. Journal of the Association for Information Science & Technology, 66(11), 2215-2222.
[10]	Bornmann, L., Wagner, C., & Leydesdorff, L. (2015). BRICS countries and scientific excellence: A bibliometric analysis of most frequently cited papers. Journal of the Association for Information Science & Technology, 66(7), 1507-1513.
[11]	Boyack, K.W., Eck, N.J., Colavizza, G., & Waltman, L. (2018). Characterizing in-text citations in scientific articles: A large-scale analysis. Journal of Informetrics, 12(1), 59-73.
[12]	Casanova, L., Cornelius, P.K., & Dutta, S. (2018). Financing entrepreneurship and innovation in emerging markets. Salt Lake city: Academic Press, 185-218.
[13]	Cbinsights. (2020). The Global Unicorn Club Current Private Companies Valued At $1B+ (including whisper valuations). Retrieved from https://www.cbinsights.com/research-unicorn-companies.
[14]	Citation Thresholds. (2020). archive.sciencewatch.com/ [Online]. Retrieved from: http://archive.sciencewatch.com/about/met/thresholds/
[15]	Comins, J.A., & Leydesdorff, L. (2017). Citation algorithms for identifying research milestones driving biomedical innovation. Scientometrics, 110(3), 1495-1504.
[16]	Csajbók, E., Berhidi, A., Vasas, L., & Schubert, András. (2007). Hirsch-index for countries based on essential science indicators data. Scientometrics, 73(1), 91-117. doi: 10.1007/s11192-007-1859-9
[17]	Cugurullo, F., Datta, A., & Shaban, A. (2016). Mega-urbanization in the global south: Fast cities and new urban utopias of the postcolonial state. New York: Routledge, 23(3), 66-80.
[18]	Davis, R.A., & Cunningham, P.S. (1990). Creative thought in neurosurgical research: The value of citation analysis. Neurosurgery, 26(2), 345-353.
[19]	de Solla Price, D.J. (1965). Networks of scientific papers. Science, 149(3683), 510-515. doi: 10.1126/science.149.3683.510 pmid: 14325149
[20]	Elbarouni, B., Ducas, J., Friesen, D., & Zhang, H. (2017). The uninterrupted anticoagulation in coronary catheterization (unicorn) registry. A single center experience. Canadian Journal of Cardiology, 33(10), S144-S145.
[21]	Essential Science Indicators. (2020). clarivate.com. Retrieved from: https://clarivate.com/products/essential-science-indicators/.
[22]	Fu, H.Z., Chuang, K.Y., Wang, M.H., & Ho, Y.A. (2011). Characteristics of research in China assessed with essential science indicators. Scientometrics, 88(5), 841-862.
[23]	Karakülah, G., Arslan, N., Yandım, C., & Suner, A. (2019). TEffect R: An R package for studying the potential effects of transposable elements on gene expression with linear regression model. Peer J, 7, 6-20.
[24]	Garfield, E. (1972). Citation analysis as a tool in journal evaluation: Journals can be ranked by frequency and impact of citations for science policy studies. Science, 178(4060), 471.
[25]	Garfield, E. (1979). Citation Indexing: Its theory and application in science, technology and humanities. New York: Wiley.
[26]	Garfield, E. (1979). Is citation analysis a legitimate evaluation tool? Scientometrics, 1(4), 359-375.
[27]	Garfield, E. (1979). Trends in biochemical literature. Trends in biochemical literature, 4(12), N290.
[28]	Garfield, E. (1991). A citation analysis of Austrian medical-research and wiener-klinishe wochenschrift. Wiener Klinische Wochenschrift, 103(11), 318-325. pmid: 1858382
[29]	Garfield, E., Malin, M.V., & Small, H. (1978). Citation data as science indicators. In Y. Elkana, J. Lederberg, R.K. Merton, A. Thackray, & H. Zuckerman (Eds.), Toward a metric of science: The advent of science indicators, 179-207. New York: Wiley.
[30]	González-Betancor, S.M., & Dorta-González, P. (2017). An indicator of the impact of journals based on the percentage of their highly cited publications. Online Information Review, 41, 398-411.
[31]	Glänzel, W., & Meyer, M. (2003). Patents cited in the scientific literature: An exploratory study of ‘reverse' citation relations. Scientometrics, 58(2), 415-428.
[32]	Grimwade, A., & Garfield, E. (2002). The Scientist on the Web. Scientist, 16(16), 10.
[33]	Guerrero-Bote, V.P., & Moya-Anegón, F. (2012). A further step forward in measuring journals' scientific prestige: The SJR2 indicator. Journal of Informetrics, 6(4), 674-688.
[34]	Harzing, A.W. (2015). Health warning: Might contain multiple personalities—The problem of homonyms in Thomson Reuters essential science indicators. Scientometrics, 105(3), 2259-2270.
[35]	Harhoff, D., Narin, F., Scherer, F.M., & Vopel, K. (1999). Citation frequency and the value of patented inventions. Review of Economics and Statistics, 81(3), 511-515.
[36]	Hemmelgarn, B.J., Setser, M.E., & Shelton, IV.F.E. (2004). Surgical stapling instrument for laparoscopic and endoscopic clinical procedure has firing device that has a distally presented cutting edge longitudinally received between the elongated channel and the anvil. EP 1479349-A1, 2004-11-24. Retrieved from https://worldwide.espacenet.com/patent/search/family/042229108/publication/EP1479349A1?q=EP1479349A1
[37]	Highly Cited Papers. (2020). archive.sciencewatch.com. Retrieved from http://archive.sciencewatch.com/about/met/core-hcp.
[38]	Hirsch, J.E. (2010). An index to quantify an individual's scientific research output that takes into account the effect of multiple co-authorship. Scientometrics, 85(3), 741-754.
[39]	Huang, M., Zolnoori, M., & Balls-Berry, J.E. (2019). Technological innovations in disease management: Text mining us patent data from 1995 to 2017. Journal of Medical Internet Research, 21(4), 1-7.
[40]	Kuan, C.H., Chen, D.Z., & Huang, M.H. (2019). Bibliographically coupled patents: Their temporal pattern and combined relevance. Journal of Informetrics, 13(4), 100978.
[41]	Kuan, C.H., & Cheng, H.J. (2014). Do we miscount patent citations? An empirical study on the impact of overlooking the citations to a patent's pre-grant publication. International Conference on Industrial Engineering and Engineering Management, 1034-1037.
[42]	Laengle, S., Merigo, J.M., Miranda, J., Słowiński, R., Bomze, I., Borgonovo, E., Dysone, R.G., Oliveira, J.F., & Teunterg, R. (2017). Forty years of the European Journal of Operational Research: A bibliometric overview. European Journal of Operational Research, 262(3), 803-816.
[43]	Lander, E.S., Lauren, L.M., Birren, B., Chad, N., Michael, C.Z., Baldwin, J., Devon, K., Dewar, K., Doyle, M., & Fitzhugh, W. (2001). Initial sequencing and analysis of the human genome. Nature, 409(6822), 860-921. doi: 10.1038/35057062 pmid: 11237011
[44]	Leydesdorff, L. (2004). The evalution of research and the scietometric research program: Histroical evlution and redefinitons of the relationship. Studies in Science of Science, 22(3), 225-232.
[45]	Lee, E. (2013). Welcome to the unicorn club: Learning from billion-dollar startups. Retrieved from https://techcrunch.com/2013/11/02/welcome-to-the-unicorn-club/
[46]	Merigo, J.M., & Yang, J.B. (2017). A bibliometric analysis of operations research and management science. Omega-International Journal of Management Science, 73, 37-48.
[47]	Meyer, M. (2000). What is special about patent citations? Differences between scientific and patent citations. Scientometric, 49(1), 93-123.
[48]	Moed, H.F., Colledge, L., Reedijk, J., Moya-Anegon, Felix., Guerrero-Bote, V., Plume, Andrew., & Amin, M. (2012). Citation-based metrics are appropriate tools in journal assessment provided that they are accurate and used in an informed way. Scientometrics, 92(2), 367-376.
[49]	Moed, H.F., Luwei, M., & Nederhof, A.J. (2002). Towards research performance in the humanities. Library Trends, 50(3), 498-520.
[50]	Moral-Munoz, J.A., Lucena-Anton, D., Perez-Cabezas, V., Carmona-Barrientos, I., González-Medina, G., & Ruiz-Molinero, C. (2018). Highly cited papers in Microbiology: Identification and conceptual analysis. Fems Microbiology Letters, 365, 20.
[51]	Narin, F. (1994). Patent bibliometrics. Scientometrics, 30(1), 147-155.
[52]	Perez-Cabezas, V., Ruiz-Molinero, C., Carmona-Barrientos, I., Herrera-Viedma, E., Cobo, M.J., & Moral-Munoz, J.A. (2018). Highly cited papers in rheumatology: Identification and conceptual analysis. Scientometrics, 116(1), 555-568.
[53]	Persson, O. (1986). Online bibliometrics-a research tool for every man. Scientometrics, 10(1-2), 69-75.
[54]	Ponomareva, l.V., Williams, D.E., Hackettb, C.J., Schnell, J.D., & Haak, L.L. (2014), Predicting highly cited papers: A Method for Early Detection of Candidate Breakthroughs. Technological Forecasting and Social Change, 81, 49-55.
[55]	Price, D.S. (1963). Little science, big science. New York: Columbia University Press.
[56]	Radicchi, F., Fortuno, S., & Castellano, C. (2008). Universality of citation distributions: Toward an objective measure of scientific impact. Proceedings of the National Academy of Sciences, 105(45), 17268-17272.
[57]	Rebentisch, H., Thompson, C., Côté-Royc, L., & Moserc, S. (2020). Unicorn planning: Lessons from the rise and fall of an American ‘smart' mega-development. Cities, 101, 102686-102692.
[58]	Research areas. (2020). images.webofknowledge.com. Retrieved from: http://images.webofknowledge.com//WOKRS535R52/help/zh_CN/WOS/hp_research_areas_easca.html.
[59]	Rodriguez-Navarro, A. (2016). Research assessment based on infrequent achievements: A comparison of the United States and Europe in terms of highly cited papers and Nobel Prizes. Journal of the Association for Information Science & Technology, 67(3), 731-740.
[60]	Ruiz-Trillo, I., Burger, G., Holland, P.W.H., King, N., Lang, B.F., Roger, A.J., & Gray, M.W. (2007). The origins of multicellularity: A multi-taxon genome initiative. Trends in Genetics, 23(3), 113-118. doi: 10.1016/j.tig.2007.01.005 pmid: 17275133
[61]	Schneider, C., Rasband, W.S., & Eliceiri, K.W. (2012). NIH Image to ImageJ: 25 years of image analysis. Nature Methods, 9(7), 671-675. doi: 10.1038/nmeth.2089 pmid: 22930834
[62]	Shelton, IV.F.E. (2006). Surgical instrument e.g. endo-cutter for use during fastening of buttress pads to tissue, comprises staple applying assembly attached to elongate shaft, which includes opposing tissue compression surfaces. EP 1621141-A2, 2006-02-01. Retrieved from https://worldwide.espacenet.com/patent/search/family/035285352/publication/EP1621141A2?q=EP1621141A2
[63]	Silva, M.R. (2016). Journal impact factors for the year-after the next can be objectively predicted. Medical Express, 3(5), M160506.
[64]	Takahashi, K., & Yamanaka, S. (2006). Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell, 126(4), 663-676. pmid: 16904174
[65]	Takahashi, K. Tanabe, K., Ohnuki, M., Narita, M., Ichisaka, T., Tomoda, K., & Yamanaka, S. (2007). Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell, 131(5), 861-872. doi: 10.1016/j.cell.2007.11.019 pmid: 18035408
[66]	Tamura, K., Peterson, D., Peterson, N., Stecher, Glen., Nei, M., & Kumar, S. MEGA5: Molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Molecular Biology and Evolution, 28(10), 2731-2739. pmid: 21546353
[67]	The Lancet Digital Health. (2019). Unicorns and cowboys in digital health: The importance of public perception. The Lancet Digital Health, 1(7), e319. pmid: 33323201
[68]	Tijssen, R.J.W. (2001). Global and domestic utilization of industrial relevant science: Patent citation analysis of science-technology interactions and knowledge flows. Research Policy, 30(1), 35-54.
[69]	Wang, G.Y., Hu, G.Y., Li, C.F., & Tangd, L. (2018). Long live the scientists: Tracking the scientific fame of great minds in physics. Journal of Informetrics, 12(4), 1089-1098.
[70]	White, H.D. (2015). Co-cited author retrieval and relevance theory: Examples from the humanities. Scientometrics, 102(3), 2275-2299.
[71]	Wharton, G.A., Sood, H.S., Sissons, A., & Mossialos, E. (2019). Virtual primary care: Fragmentation or integration? The Lancet Digital Health, 1(7), e330-e331. doi: 10.1016/S2589-7500(19)30152-9 pmid: 33323207
[72]	White, H.D., Boell, S.K., & Yu, H. (2009). Libcitations: A measure for comparative assessment of Book Publications in the Humanities and Social Sciences. Journal of The American Society for Information Science & Technology, 60(6), 1083-1096.
[73]	Wikipedia. (2020). Unicorn From Wikipedia, the free encyclopedia. Retrieved from https://en.wikipedia.org/wiki/Unicorn.
[74]	Wikipedia. (2020). Unicorn (finance) From Wikipedia, the free encyclopedia. Retrieved from https://en.wikipedia.org/wiki/Unicorn_(finance).
[75]	Ye, S.Q., Xing, R., Liu, J., & Xing, F.Y. (2013). Bibliometric analysis of Nobelists' awards and landmark papers in physiology or medicine during 1983-2012. Annals of Medicine, 45(8), 532-538. pmid: 24195599
[76]	Zeng, C.J., Qi, E. P., Li, S.S., Stanley, H.E., & Ye, F.Y. (2017). Statistical characteristics of breakthrough discoveries in science using the metaphor of black and white swans. Physica A, 487, 40-46.
[77]	Zhang, H.H., Zuccala, A.A., & Ye, F.Y. (2019). Tracing the ‘Swan-groups' of Physics and Economics in the Key Publications of Nobel Laureates, Scientometrics, 119, 425-436.
[78]	Zhang, J.A., Vogeley, M.S., & Chen, C.M. (2011). Scientometrics of big science: A case study of research in the Sloan Digital Sky Survey. Scientometrics, 86(1), 1-14.
[79]	Zou, C., & Peterson, J.B. (2016). Quantifying the scientific output of new researchers using the zp-index. Scientometrics, 106(3), 901-916.

Year	Scientific papers			Technical patents
Year	WoS total papers	Absolute unicorn number	Ur: Relative unicorn ratio (%)	DII total patents	Absolute unicorn number	Ur: Relative unicorn ratio (%)
2000	874,542	2	0.0002	672,139	33	0.0049
2001	872,370	5	0.0006	729,168	21	0.0029
2002	889,519	4	0.0004	786,869	12	0.0015
2003	927,047	6	0.0006	791,486	16	0.0020
2004	967,440	11	0.0011	824,382	13	0.0016
2005	1,016,231	6	0.0006	893,139	22	0.0025
2006	1,070,302	8	0.0007	924,045	17	0.0018
2007	1,122,363	13	0.0012	1,085,298	30	0.0028
2008	1,201,425	15	0.0012	1,163,732	41	0.0035
2009	1,251,718	30	0.0024	1,224,936	12	0.0010
2010	1,294,375	28	0.0022	1,384,960	3	0.0002
2011	1,373,399	16	0.0012	1,473,876	1	0.0001
2012	1,441,144	21	0.0015	1,774,920	3	0.0002
Total	14,301,875	165	0.0012	13,728,950	224	0.0016

Year/Biomedical unicorns	Scientific papers		Technical patents
Year/Biomedical unicorns	Absolute number	Relative ratio (%)	Absolute number	Relative ratio (%)
2000	2	0.0002	5	0.0007
2001	2	0.0002	6	0.0008
2002	2	0.0002	1	0.0001
2003	4	0.0004	1	0.0001
2004	6	0.0006	1	0.0001
2005	3	0.0003	9	0.0010
2006	3	0.0003	10	0.0011
2007	7	0.0006	24	0.0022
2008	5	0.0004	35	0.0030
2009	19	0.0015	10	0.0008
2010	18	0.0014	3	0.0002
2011	8	0.0001	0	0.0000
2012	16	0.0002	1	0.0001
Total	95	0.0007	106	0.0008

Code	Title	Author(s)	Source	CT
Pr1	Initial sequencing and analysis of the human genome	Lander, ES et al.	NATURE 2001, 409(6822):860 -921.	8,725
Pr2	Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin	Knowler, WC; Barrett-Connor, E; Fowler, SE; et al.	NEW ENGLAND JOURNAL OF MEDICINE. 2002, 346(6):393-403.	5,151
Pr3	Measuring inconsistency in meta-analyses	Higgins, JPT; Thompson, SG; Deeks, JJ; et al.	BRITISH MEDICAL JOURNAL 2003, 327(7414):557-560	5,443
Pr4	MicroRNAs: Genomics, biogenesis, mechanism, and function	Bartel, DP	CELL 2004, 116(2):281-297.	8,688
Pr5	Arlequin (version 3.0): An integrated software package for population genetics data analysis	Excoffier, Laurent; Laval, Guillaume; Schneider, Stefan	EVOLUTIONARY BIOINFORMATICS 2005, 1:47-50.	7,808
Pr6	Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors	Takahashi, Kazutoshi; Yamanaka, Shinya	CELL 2006, 126(4):663-676.	8,826
Pr7	Induction of pluripotent stem cells from adult human fibroblasts by defined factors	Takahashi, Kazutoshi; Tanabe, Koji; Ohnuki, Mari; Narita, et al.	CELL 2007, 131(5):861-872.	8,029
Pr8	Analyzing real-time PCR data by the comparative C-T method	Schmittgen, Thomas D.; Livak, Kenneth J.	NATURE PROTOCOLS 2008, 3(6):1101-1108.	7,665
Pr9	MicroRNAs: Target Recognition and Regulatory Functions	Bartel, David P.	CELL 2009, 136(2):215-233.	10,328
Pr10	PHENIX: a comprehensive Python-based system for macromolecular structure solution	Adams, Paul D.; Afonine, Pavel V.; Bunkoczi, Gabor; et al.	ACTA CRYSTALLOGRAPHICA SECTION D-STRUCTURAL BIOLOGY 2010, 66(2):213-221.	11,194

Code	Scientific papers		Technical patents
Code	Eq. (3)	Eq.(2)	Eq. (3)	Eq.(2)
B	121.364	121.364	8.057	8.057
a	19.895	148.005	8.988	13.196
Obs	805	805	1008	1008
R²	0.650	0.642	0.541	0.522
R²_adj	0.609	0.600	0.490	0.469
RSE	506.307	506.307	24.372	24.372
F	15.897	15.362	10.562	9.793

Code	Scientific papers		Technical patents
Code	theoretical	empirical	theoretical	Empirical
P1	7,205	8,204	453	593
P2	6,755	6,746	444	554
P3	13,028	8,725	426	617
P4	11,354	5,813	417	511
P5	7,619	7,062	426	556
P6	7,286	5,151	462	832
P7	6,035	8,339	498	542
P8	7,421	7,661	543	751
P9	7,367	8,688	516	566
P10	6,089	6,463	444	507
RMSE	0.2127	0.2127	0.0923	0.0923