1
Q
what main failures are associated w the exam
A
- not doing a complete analysis of the unnown print
- lack of documentation of ACE process
- verification process lacking in QA/QC
2
Q
Evidence can be considered _____ (faulty/misleading) when the testimony is not supported by the science
A
faulty
3
Q
Evidence can be _____ (faulty/misleading) when opinions/conclusions are overstated or the limitations of the evidence are not clearly stated
A
misleading
4
Q
what is faulty evidence
A
when the testimony is not supported by the science
5
Q
what is misleading evidence
A
when opinions/conclusions are overstated or the limitations of the evidence are not clearly stated
6
Q
true/false fingerprint permanency is supported by scientific literature
A
true
7
Q
what did Hermann Welcker 1856-1897 do
A
found the impressions to be identical in detail
8
Q
what studies have supported fingerprint permanency
A
- Welcker 1856-1897
- Faulds (1880)
- Galton (1892)
- Herschel (1916)
- Okajima (1979)
- Wan et al (2003)
- Wetheim et al (2002)
9
Q
when can permanent change happen to the appearance of the ridge detail
A
- damage to the dermis layer only real change
- aging
- some meds
- human growth
10
Q
how does aging influence prints
A
- surface ridges flatten
- loss of elasticity in the dermis (skin becomes flaccid)
- ridge pattern is less visible
11
Q
who studied how ridge patterns are less visible after aging
A
Okajima 1979
12
Q
how can meds affect prints
A
some have the side effect of removing ridge detail
13
Q
who designed the first print probability model and when
A
Sir francis galton in 1892
14
Q
how many print probability models have been developed
A
about 24
15
Q
describe the Galton model (1892)
A
- very basic if not crude
- built on his abillity to predict the occurance of ridge characteristics depending on the configuration of surrounding ridges
- not based on actual frequencies and distributions of ridge characteristics
16
Q
Based on Galton’s calculations, the probability of finding any given arrangement of ridge characteristics in a fingerprint was what
A
1 in 68 billion
17
Q
true/false the galton model (1892) was based on the frequencies and distributions of ridge characteristics
A
false
18
Q
describe the Henry Model (1900)
A
- proposed each ridge characteristic was independent, identically distributed event
- each rc event had a prob of 0.25
- the prob of finding 12 matching rc was then 1 in 17 million
19
Q
in the henry model, what was the prob of finding 12 matching characteristics
A
1 in 17 million
20
Q
how was pattern type accounted for in the henry model
A
- made it equal to 2 more ridge characteristics
- so previous result is multiplied by 1/16 (1/4 * 1/4)
21
Q
describe the Balthazard’s Numerical Standard (1911)
A
- minimum 17 rc required to identify an individual
- used a probabilistic model and estimated population of 1.5 billion
- suggested number could be reduced if the suspect population was limited to a town or country
22
Q
what did Dr. Victor Balthazard (1911) do
A
made the first numerical standard for print identification
23
Q
true/false in the Balthazard’s numerical standard (1911), the estimated population is fixed to 1.5 billion
A
- false
- could be reduced if the suspect population was limited to a town or country
24
Q
describe the Locard’s Tripartite Rule aka locard model
A
- if more than 12 concurring rc are present and the print is very clear, then the certainty of identity is beyond debate
- If 8 to 12 concurring minutiae are found, then identification is
marginal and certainty of identity is dependent on: other things
a. the quality (clarity) of the fingerprint,
b. the rarity of the minutiae type,
c. the presence of a core and delta in a clear area of the print,
d. the presence of pores, and
e. the perfect agreement of the width of the ridges and furrows, the direction of the ridge flow, and the angular value of the bifurcation. - If a limited number (< 8) of characteristic features are present,
* the fingerprint cannot provide certainty for an identification,
* but only a presumption proportional to the number of points
available and their clarity
25
**true/false** the locard model is a statistical model
false
26
describe the Locard's Tripartite Rule, certainty of identity depends on what if 8-12 concurring minutiae are found
a. the quality (clarity) of the fingerprint,
b. the rarity of the minutiae type,
c. the presence of a core and delta in a clear area of the print,
d. the presence of pores, and
e. the perfect agreement of the width of the ridges and furrows, the direction of the ridge flow, and the angular value of the bifurcation.
27
in locard's tripartite rule, when can positive identification be established
- in parts 1 and 2 of the rule
- following discussion of the case by at least 2 competent and experiences examiners
28
part 3 of locard's tripartite rule is highly suggestive of what
a probabilistic approach to print evidence and conclusions
29
**true/false** probabilistic models have been validated in operational settings
false
30
what is the main thing all probability models share
they reach very small probabilities that two individuals will share the same arrangement of ridge characteristics
31
**true/false** drugs can be detected in print residues
true
32
what drugs can be detected in a single print
- cocaine
- heroin
- morphine
- prescription meds
33
how have studies linked residues to age of the print
- traced shifting levels of triacylglycerols in donors using mass spec
- could determine the degredation rate for each person over 7 days
- but rate differed among donors
- method worked on residues that have been dusted w powder
34
**true/false** in studies on ages of prints, degradation rates stayed the same b/w people
false
35
**true/false** in studies on ages of prints, methods worked on residues that have been dusted w powder
true
36
when were new polymer bills introduced
2015
37
how do you treat old bills for prints
- ninhydrin
- indanedione
- *and other methods*
38
how do you treat new polymer bills
- **CA fuming**
- *but limited to the transparent areas of the banknotes*
- **vacuum metal deposition (VMD)**
- *for opaque, ink covered, areas of the banknotes*
39
what does VMD stand for and what is it
- **vacuum metal deposition**
- gold is vaporized
- which adheres to the fats and oils in the print
- vaporized reflective zinc then adheres to the gold
40
what is an alternative to VMD
- Natural1 IR powder and a forensic light source
- silicone casting material and gelatin lifts
41
what does FRStat stand for and how did it come to be
- **statistical software for fingerprints**
- developed by **DFSC** defense forensic science center
- in response to criticisms about lack of demonstrable basis to make conclusions in pattern evidence
42
what is FRStat
a tool to provide statistical estimate to the strength of evidence along w the examiners own conclusions
43
**true/false** FRStat has limitations
- **true**
- only as good as the info entered
44
what must be done before FRStat is adopted by an agency
needs to be internally validated for use
45
**true/false** sex can be determined from print residue
true
46
how can sex be determined from print residue
- levels of certain AA in prints are 2x as high in female sweat than men
- *research is ongoing, trying to make it a simple test from the field*
47
what did Christophe Champod do
- wrote an aticle in 2015
- about print identification
- advances since the NAS report in 2009
48
In Champod's paper, how many areas were there in section 5
6
49
In Champod's paper, which section is most of interest to us
- section 5
- "a way forward?"
50
what were the 6 areas of interest In sec. 5 of Champod's paper
1. clarifying the inference process
2 improving transparency
3. moving away from considering experts as black boxes
4. introducing stats and resolving potential conflicting opinions
5. being able to rank marks as a function of their level of quality
6. managing the potential of bias
51
describe "1. clarifying the inference process" from champod's paper
- abandon the identification conclusion altogether
- suggests using a bayesian framework (like stats and probability)
- an evaluation of findings by assigning 2 probabilities
52
describe "2. Improving transparency" from champod's paper
- disclosure regarding case files, report writing, and presentation of findings in court
- find a way to articulate the weight assigned to each feature without resorting to statements like "theyre unique or its my opinion based on my training"
53
describe "3. Moving away from considering experts as black boxes" from champod's paper
- practitioner error rates vs practice wide error rates
- believes false pos rate of 0.1% is so low that the probability of an error will be dismissed
- process offers no mechanism to acc measure the weight to be attached
54
describe "4. introducing stats and resolving potential conflicting opinions" from champod's paper
- stats are unavoidable for next gen of print evidence
- both scientifically and logically
- cant replace print examiners, but foresees intro in court of *probability based print evidence*
- more research is needed cause there are no validated published models
55
describe "5. Being able to rank prints as a function of their level of quality" from champod's paper
- hard to measure the info content of a mark
- so we need to develop agreed systematic methods to measure quality
56
describe "6. Managing the potential of bias" from champod's paper
- mechanisms allowing us to guard against bias should be proportional to the info content of the prints
- if the quality is *high* in info, the risk of bias is limited
- if the quality is *low*, all efforts should be put in place in order to mitigate bias and pressure
57
what is a key challenge of introducing probability based print evidence
- training
- court
58
how little drugs can we identify drugs from prints
tens of pg
59
Fingerprinting
flashcards
Decks in class (16)
# Cards
-
Photography review75
-
Latent Print Development73
-
Case study5
-
Recording Fingerprints (Lab 1)20
-
History and Composition180
-
case study 21
-
Comparison Process79
-
Searching, Documenting and Report Writing74
-
Proficiency Testing and Error Rates70
-
Case Study: Nov 103
-
Expert Opinion Evidence & Court27
-
case study: r v bornyk41
-
case study: idk in class one16
-
Errors and Bias- QA73
-
Research & Statistics59
-
Canadian Case Study49
