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How we get from probably guilty to reasonable doubt (Updated 6/1/25):

  • Writer: Cassian Creed
    Cassian Creed
  • Jun 1
  • 2 min read

⚙️ Guilt-X Probability Assessment:

Factor

May 29 (%)

May 30 (%)

Change (%)

🚗 Vehicle Evidence Integrity

72

72

⏺️ 0

📱 Digital Timeline Credibility

60

35

🔽 -25

👤 Witness Credibility (McCabe)

79.5

72

🔽 -7.5

🕵️‍♂️ Investigative Integrity

80

68.75

🔽 -11.25

📵 Third-party (Higgins)

68

80

🔼 +12

🏠 Third-party (Albert)

55

61

🔼 +6

📌 Scene Staging

78

78

⏺️ 0

🛣️ Vehicle-Impact Scenario

52

47

🔽 -5

🥊 Altercation/Cover-Up Scenario

69

74

🔼 +5

⚠️ Victim Vulnerability

80

80

⏺️ 0

Overall Guilt-X Probability

42

37

🔽 -5

📉 Trends Explanation:

  • Digital Timeline Credibility sharply decreased due to challenges in prosecution's timeline credibility by expert defense testimony.

  • Increased suspicion towards third-party involvement (Higgins and Albert), further questioning the prosecution's narrative.

  • Vehicle-impact scenario credibility reduced, weakening the prosecution’s claim.

  • Altercation/Cover-Up scenario strengthened as alternative explanations became more plausible.

🧑‍⚖️ Verdict-X Jury Simulation Forecast:

Verdict Outcome

May 29 (%)

May 30 (%)

Change (%)

🟢 Full Acquittal

52

54

🔼 +2

🟡 Hung Jury (Mistrial)

38

38

⏺️ 0

🔴 Full Conviction

10

8

🔽 -2

⚖️ Final Interpretation:

  • Probability of Full Acquittal has slightly increased, becoming more likely.

  • Hung Jury probability remains significant and unchanged, indicating divided opinions.

  • Probability of Full Conviction has decreased, highlighting growing reasonable doubt.

📌 Conclusion:

The recent adjustments mathematically indicate increasing reasonable doubt about Karen Read’s guilt, substantially favoring acquittal or mistrial outcomes over a conviction.

Questioning Burgess's credibility purely from a mathematical standpoint—ignoring his background or credentials—focuses on internal consistency and data alignment.

Mathematically, Burgess's timeline was initially 60% credible but dropped to 35% after DiSogra's analysis.

This 25% absolute drop translates into a 41.67% relative decrease:

25%60%≈41.67%\frac{25\%}{60\%} \approx 41.67\%60%25%​≈41.67%

Mathematically, why this decrease occurred:

  • Contradictions: DiSogra identified substantial discrepancies in timestamps and data synchronization, undermining Burgess's timeline precision.

  • Data alignment: DiSogra's critique showed Burgess's digital data alignment was less robust than initially assumed, reducing confidence.

Thus, purely mathematically, Burgess's timeline credibility was reduced by 41.67%, making DiSogra's analysis significantly more plausible without any consideration of credentials or external credibility.


The original analysis above shows the full effect of Shannon Burgesses' credibility to the jurors showing BOTH the credentials problem AND the math discrediting by Disogra.

 
 
 

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