1.    Oracle ThinkQuest Education Foundation, Probability Central, Independent Variables.

2.    Christophe Champod, Chris Lennard, Pierre Margot and Milutin Stoilovic, Fingerprints and Other Ridge Skin Impressions, 7.

3.    William J. Babler, PhD, Baylor College of Dentistry, Dallas, TX 75246, Embryologic Development of Epidermal Ridges and Their Configurations, 100.

4.    David Ashbaugh, Quantitative-Qualitative Friction Ridge Skin Analysis, 1999 CRC Press

5.    Henry C. Lee and R.E. Gaensslen, Champod and Margot Model (1995 – 1996), Advances in Fingerprint Technology, Second Edition, 373-378.

6.    Wolfram MathWorld, the web’s most extensive mathematics resource, Law of Large Numbers.

7.    James W. Osterburg, Development of a Mathematical Formula for the Calculation of Fingerprint Probabilities Based on Individual Characteristics, Journal of the American Statistical Association, December 1977, Vol. 72, No. 360, Applications Section.

8.    Harold Cummins, Dermatoglyphics: Significant Patternings of the Body Surface, Yale Journal of Biology and Medicine 73 (2000), pp. 80.

9.    David A. Stoney, Ph.D. and John I. Thorton, A Critical Analysis of Quantitative Fingerprint Individuality Models, Journal of Forensic Sciences, JFSCA, Vol. 31, No.4, Oct. 1986, 1212.

10.    Sargur N. Srihari and Harish Srinivasan, Individuality of Fingerprints:  Comparison of Models and Measurements, Center of Excellence for Document Analysis and Recognition, Department of Computer Science and Engineering, University at Buffalo, The State University of New York, Buffalo NY, USA.

11.    Random.org, V2.0 beta, True Random Number Service, Random.org, Die Roller.

12.    J. Hess, LAPD Latent Finger Print Section, The Reference Shelf (Santamaria Discussion), CLPEX, http://www.clpex.com/, “A New Method of Evaluating Ridge Characteristics.” By Florentino Santamaria Beltran, Chief of the Technical Police Laboratory in Madrid, Spain, (Originally printed in Finger Print and Identification Magazine, Vol. 52 No.; April 1971).

13.    Interpol European Expert Group on Fingerprint Identification - IEEGFI II, Pattern Force, 7.6.2.

14.    Zeising, Adolf, Golden ratio, Nature, Neue Lehre van den Proportionen des meschlischen Körpers, Leipzig, 1854, preface.

15.    Welcome to the Museum of Harmony and Golden Section, Golden Section, Nature and a Man, The “Golden” spirals and “pentagonal” symmetry in the alive Nature.

16.    wikipedia.org, Golden Ratio.

17.    Interpol European Expert Group on Fingerprint Identification - IEEGFI II, Pattern Force 7.6.1.

18.    David Ashbaugh, Poroscopy, Identification News, November 1982.

19.    David Ashbaugh, Forensic Ridgelogy, Portland, Oregon, 11/27 - 12/1/06.

20.    Pat A. Wertheim, Santa Barbara, California 3/11 - 3/13/02, Analysis of Problem Latents, Workbook, 12.

21.    IAFIS Presentation, Chesapeake Bay Division of the IAI, 2007.

22.    Ed German, Latent Print Examination, Fingerprints, Palmprints and Footprints, Home, Problem Idents.

23.    Kasey Wertheim, Complete Latent Print Examination, Close Calls (best non's).

24.    Henry Templeman, Senior Latent Print Examiner, San Jose Police Department, Central Identification Unit.

25.    Michelle Battaglia, Latent Print Examiner I, San Jose Police Department, Central Identification Unit.

26.    John "Dusty" Clark, Journal of Forensic Identification, Vol. 52, No. 4.

27.    Interpol European Expert Group on Fingerprint Identification – IEEGFI,
Method For Fingerprint Identification, Definitions, No. 10, Look-a-likes.

28.    Interpol European Expert Group on Fingerprint Identification – IEEGFI,
Method for Fingerprint Identification, Empirical Standard Approach, Sufficient Information, Paragraph 4.

29.    Christophe Champod, Edmond Locard - Numerical Standards & "Probable" Identifications, Journal of Forensic Identification, 45 (2) 1995, 136-155.

30.    David A. Stoney, Ph.D., A Critical Analysis of Quantitative Fingerprint Individuality Models, 1214-1215.

31.    Marian M. Price, FBI Training Instructor, Universal Latent Workstation (ULW) Training, reported FBI IAFIS criminal fingerprint database as approximately 530 million.

32.    John “Dusty” Clark, retired from State of California Department of Justice, reported DOJ AFIS criminal fingerprint database as approximately 63,500,000.

33.    William Nasiatka, Latent Fingerprint Examiner Supervisor, San Jose Police Department, Central Identification Unit, reported Santa Clara County AFIS criminal database as approximately 5,500,000.

34.    Christophe Champod, The Inference of Identity of Source:  Theory and Practice, assistant professor, Institut de Police Scientifique et de Criminologie, University de Lausanne, BCH, CH-1015 Lausanne-Dorigny (Switzerland).

35.    SWGFAST, Scientific Working Group on Friction Ridge Analysis, Study and Technology (09/11/03 ver 1.0), SWGFAST Standards for Conclusions, Basic Principle 1.2.1.

36.    SWGFAST, Scientific Working Group on Friction Ridge Analysis, Study and Technology, Glossary – Consolidated (9/9/03 ver 1.0), SWGFAST Glossary.

37.    FBI Laboratory, Latent Print Operations Manual, Examining Friction Ridge Impressions, Issue date: 10/12/2005.

38.    Association of Firearms and Tool Mark Examiners, Theory of Identification as it Relates to Toolmarks, AFTE Journal, Vol.30, No. 1, Winter 1998, 86-88.

39.    Interpol European Expert Group on Fingerprint Identification – IEEGFI,
Method for Fingerprint Identification, Holistic approach to identification of the friction ridge surface, paragraph 6, Empirical Standard Approach, Sufficient Information, Paragraph 4. 

40.    International Association for Identification (IAI), IAI Position Concerning Latent Fingerprint Identification, Identification News, Vol. 38 No. 1, 2008.

41.    The International Association for Identification (IAI), Friction Ridge Skin Identification Training Manual.

42.    SWGFAST, Scientific Working Group on Friction Ridge Analysis, Study and Technology, SWGFAST Standards for Conclusions and SWGFAST Training To Competency for Latent Print Examiners.

43.    John “Dusty” Clark, Sufficiency for Conclusions.
    
44.    Interpol European Expert Group on Fingerprint Identification – IEEGFI,
Method for Fingerprint Identification, Second part of the mandate: 'an agreed number of minutiae and other characteristics', No. 1 and 2.

45.    FBI Forensic Science Communications, Review of the Scientific Basis for Friction Ridge Comparisons as a Means of Identification:  Committee Findings and Recommendations, II.B. Uniqueness of Friction Ridge Patterns, pg 4, January 2006–Volume 8–Number 1.

46.    Federal Bureau of Investigation, U.S. Department of Justice, An Analysis of Standards in Fingerprint Identification, FBI Law Enforcement Bulletin, June 1972.

47.    Scott, Walter R., Fingerprint Mechanics, Springfield, IL, 1951 pp. 62-63

48.    Wentworth, Bert and Wilder, Harris H., Personal Identification, 1932, pp. 262-263.

49.    Federal Bureau of Investigation, U.S. Department of Justice, An Analysis of Standards in Fingerprint Identification, FBI Law Enforcement Bulletin, June, 1972.

50.   Sandy L. Zabell, Ph.D., Fingerprint Evidence, pg. 154, (re:Paul Meehl, Clinical Versus Statitical Prediction: A Theoretical Analysis and Review of Evidence (Jason Aronson ed. Univeristy of Minnesota. Press.) 

51.  Sarah Light, staff writer, The Albert Lea Tribune, Scientist: Robert's prints are on gun, Oct. 17, 2006.

52.  Simon A. Cole, More Than Zero:  Accounting for Error in Latent Fingerprint Identification, The Journal of Criminal Law & Criminology, Vol. 95, No. 3.

53.  William M. Grove and Martin Lloyd, Meehl's Contribution to Clinical Versus Statistical Prediction, Journal of Abnormal Psychology, 2006, Vol. 115, No.2, 192-194.   

54.  Wikipedia, Fingerprint: Criticism.

55.  State of Maryland v. Brian Rose, Circuit Court of Baltimore County, Case No. K06-0545, Memorandum Decision. 

56.  State of Maryland v. Lamont Anthony Johnson, Circuit Court for Howard County, Criminal Case No. 07-47108, Order.

57.  Shirley McKie, www.shirleymckie.com/index.htm 

58. Brandon Mayfield, http://en.wikipedia.org/wiki/Brandon_Mayfield

59. Simon A. Cole, Out of the Daubert Fire and into the Fryeing Pan? Self-Acceptance versus Meta-Expertise and the Admissibility of Latent Print Evidence in Frye Jurisdictions, Tables 1-3, October 14, 2007, Minnesota Journal of Law, Science & Technology, Vol. 9, No. 2, 2008.

60. Michelle Triplett, Michele Triplett's Fingerprint Terms.

61.  Scientific Working Group for Friction Ridge Analysis, Study and Technology, SWGFAST,  Validation of Research and Technology.

62. Steve Scarborough, Ray York, Kasey Wertheim, Daubert Card, www.clpex.com 

63. Human Factors Consultants, Error Rates for Human Latent Fingerprint Examiners, http://www.humanfactorsconsultants.com/errorrates.doc

64. The International Association for Identification, Current Affairs, State of Maryland v. Bryan Rose,  Memorandum Decision Re Reconsideration, Circuit Court for Baltimore County, Case No. K06-0545.

65.  Robert Niles, Survey Samples Sizes, SensibleTalk.com "Analysis from the reality-based world"

66.  Charles R. Kingston and Paul L Kirk, School of Criminology, University of California, Berkeley, United States, Historical development and evaluation of the "12 point rule" in fingerprint identification, pdf.

67.  Image from Jean-Francois Mainguet, Fingerprint algorithms, Algorithmes de reconnaissance d'empreintes digitales.  

68.  Dr. Ralph Haber, Voir dire examination by Ms Dever:  Baltimore County Circuit Court, State of Maryland versus Brian Rose, May 30, 2007, before Honorable Susan Souder, Associate Judge, pg. 102, lines 10-13.

69.  B. Bindra, OP Jasuja and AK Singla, Poroscopy: A Method of Personal Identification Revisited,  Anil Aggrawal's Internet Journal Of Forensic Medicine and Tocicology, 2000; Vol.1, No.1.

70.  Mark A. Acree, People v. Jennings:  A Significant Case In American Fingerprint History, MS Forensic Science, University of Alabama at Birmingham.

71.  Pat A. Wertheim, Scientific Comparison and Identification of Fingerprint Evidence (Paper given as a lecture, at The Fingerprint Society Lectures, Liverpool, 17-19^th March 2000), Fingerprint Whorld, Vol. 26, No. 101, July 2000, 95-106.

72.  Alexandre Anthonioz, Nicole Egli, Christophe Champod, Cedric Neumann, Roberto Puch-Solis, Adie Bromage-Griffiths, Level 3 Details and Their Role in Fingerprint Identification:  A Survey among Practitioners, Journal of Forensic Identification, 562-589, 58 (5) 2008.

73.  David S. Kidder and Noah D. Oppenheim, The Intellectual Devotional, The Normal Curve, pg. 354. 

74.  Ian Ayres, Super Crunchers:  Why Thinking by the Numbers is a New Way to be Smart, Experts Versus Equations, pp 103-128.

75.  Ian Ayres, Super Crunchers Presentation, Google Headquarters, Mountain View, CA, 11/08/2007, YouTube.

76.  Michael A. Bishop and J. D. Trout, Trout and Bishop, 50 Years of Successful Predictive Modeling Should Be Enough: Lessons for Philosophy of Science, Iowa State University and Loyola University, Chicago.

77.  U.S. Department of Justice Office of the Inspector General, A Review of the FBI's Handling of the Brandon Mayfield Case, Chapter Four, pg. 130.

78.  Standard Deviation Calculator, http://invsee.asu.edu/srinivas/stdev.html

79.  Confidence Interval for Means Calculator,   http://www.dimensionresearch.com/resources/calculators/conf_means.html

80.  Michael Kucken and Alan Newell, A model for fingerprint formation, Europhysics Letters, 68 (1), pp. 141-146 (2004).

81.  Colin Aitken and Franco Taroni, Statistics and the Evaluation of Evidence for Forensic Scientists, pg 276 – 278.

82.  Colin Aitken and Franco Taroni, Statistics and the Evaluation of Evidence for Forensic Scientists, pg 285.

83.  Keith Devlin, The Myth That Will Not Go Away, Mathematician and Executive Director of the Center for the Study of Language and Information at Stanford University. [Link]

84.   Jenifer A.L. Smith, Ph.D., and Bruce Budowle, Ph.D., Source Identification of Body Fluid Stains Using DNA Profiling, FBI Laboratory.

85. David J. Balding, Ph.D. and Peter Donnelly, Ph.D., Evaluating DNA Profile Evidence When the Suspect is Identified Through a Database Search, ASTM International, 1996.

86.  Christophe Champod, The Inference of Identity of Source:  Theory and Practice

87. Evett I.W., Weir, B.S., Interpreting DNA Evidence – Statistical Genetics for Forensic Scientists, Sunderland: Sinauer Associates, Inc. Sunderland, 1998

88.  Nassim Nicholas Taleb, Fooled by Randomness, pg. 216.

89.  Francis Galton, Fingerprints, pg. 110.

90.  Fingerprint Consultants,  www.onin.com/fp; The International Association for Identification, Certifications

91.  The National Academies, Badly Fragmented Forensic Science System Needs Overhaul, Full Report

92.  Stanford Encyclopedia of Philosophy, Karl Popper, [link]

93.  Karl Popper, Conjectures and Refutations, pg. 48.

94.  Illinois v. Cory Safford [link].

95.  SWGFAST, Glossary, 2.0 PDF, 05/08/09, posted 07/28/09.

96.  Cedric Neumann, Computation of Likelihood Ratios in Fingerprint Identification for Configurations of Any Number of Minutiae, [link]. 

97.  Alice V. Maceo, Analysis of Distortion in Latent Prints, 94th IAI International Educational Conference Workshop, Tampa, Florida, August 2009.

98.  Paul Chamberlain, Senior Forensic Scientist, Forensic Science Service, www.forensic.gov.uk.

99.  Ludwig Wittgenstein, Tractatus Logico - Philosophicus, pg. 49.

100. Ludwig Wittgenstein, On Certainty, pg. 2e.

101.  Criminalist Cordelia Willits, County of Santa Clara County Crime Laboratory

102.  Christophe Champod, Report to the Fingerprint Inquiry, pg 8/30 [link]

103.  Arie Zeelenberg, Personal correspondence March 7, 2010, Senior Fingerprint Advisor, National Police Force of the Netherlands.

104.  Christophe Champod, Report to the Fingerprint Inquiry, Sept. 28, 2009. [Link]

105.  Brian Cox and Jeff Forshaw, why does E=mc^2? (and why should we care?), Preface.

106.  Brian Cox and Jeff Forshaw, why does E=mc^2? (and why should we care?), pg. 21.

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The author extends his appreciation to the individuals cited in the above references for their work, comments and/or suggestion.  Each helped the author to formulate, describe and/or test the T-Model.