Plant Virology Research

Dr. Angela Thompson Smith recently participated in a scientific study where remote viewers attempted to identify sick plants from healthy plants. Titled A Triple Blind Study of the Non-Local Perception of Plants Infected with Tobacco Mosaic Virus, the study found that remote viewers could identify sick plants from healthy ones. As the protocols became more refined, Dr. Smith was able to correctly identify 80% of the sick plants, and 100% in another protocol.

Training and Solo Remote Viewing Sessions

Dr. Thompson Smith attended remote viewing training sessions with Paul Smith (Remote Viewing Systems – 1998) and Lyn Buchanan (PSI – 1999). While these training sessions were not graded, Dr. Smith assessed percentages for each session, using PSI’s data judging system. The following is a personal transcript of sessions completed during and after training. (Results tabulated March 27th, 1999.)

• RVIS Overall: 6 Training Targets 92.8%
• RVIS Overall: 10 Solo Training Targets 71.1%
• PSI Overall: 5 Training Targets 57.2%
• PSI Overall: 8 Solo Training Targets 72.2%

Lottery ARV work with Dr. James Spottiswoode and Dr. Ed May, SAIC

16 ARV sessions with rankings converted to Z scores. Trials 2 through 6 were 4 target ARVs, the remainder were 5 target ARVs. Total Stouffer’s Z for all 16 sessions was 1.57 with a p value of 0.058 (just shy of significance).

Retrocausal Psychokinesis

In studies performed as an external participant Dr. Smith took part in research that attempted to psychokinetically affect tones that had been pre-recorded at the Rhine Research Center. In a series conducted in 1986, Dr. Smith was able to significantly shift tones to a lower frequency with a z score of 1.87. The tones that were successfully lowered were Slow Piano and Organ.

Remote Perception

Sessions performed at the Princeton Engineering Anomalies Research (PEAR) Laboratory in April and May 1992 between a remote viewing participant traveling in Korea and Dr. Angela Smith resident in Princeton, NJ. Z score for Angela Smith’s sessions (involving the perception of information about the Korean locations) was significant with a Z score of 1.767. The other participant scored a highly significant Z score of 3.135 with Dr. Smith acting as sender to the participant traveling in Korea.

Stock Market ARV Predictions for a Private Client

5 ARV sessions to predict the direction of the Dow Jones. 4 of the 5 were in the correct direction (80% success rate).

Psychokinesis data (REG Database): PEAR Laboratory 1988-1992

(In compliance with PEAR requirements, Operator Number not revealed)

• All 66 Diode REG Local sessions
• Baseline Intention: Z score = 0.638 p = 0.262
• Low Intention: Z score = 1.927 p = 0.027 (significant)
• High Intention: Z score = 2.919 p = 0.002 (significant)

Psychokinesis Data Linear Pendulum: PEAR Laboratory 1988-1992

• 54 Datasets. Difference between Intention and Baseline
• Difference = 12.06, sd = 64.18, T score = 1.38, p = .09
• Ref: A Linear Pendulum Experiment: Effects of Operator Intention and Damping Rate. (1993), Nelson R., and Bradish, J. Princeton Engineering Anomalies Research. Princeton University. Technical Note PEAR 93003.

Psychic Reward PK software distributed by Dr. Jack Houck – 1993-1994

Score Summary 07/01/1993

• ESP: Z score = -0.06 Probability 4.78%
• PK: Z score = 1.99 Probability 95.34% (significant)

Score Summary 10/26/1993

• ESP: Z score = 2.21 Probability 97.28%
• PK: Z score = 2.03 Probability 95.76%
• TOTAL: Z score = 2.56 Probability 98.96% (all significant)

Score Summary 12/13/1993

• ESP: Z score = 2.00 Probability 95.44%
• PK: Z score = 2.13 Probability 96.68%
• TOTAL: Z score = 2.59 Probability 99.04% (all significant)

Score Summary 1/12/1994

• ESP: Z score = 2.00 Probability 95.44%
• PK: Z score = 2.06 Probability 96.06%
• TOTAL: Z score = 2.71 Probability 99.32% (all significant)

Psychic Reward Intention Work

Intention work with Psychic Reward to produce a Low score, a Baseline score, and a High score, in that order.

• Low Score: Z score = -1.12
• Baseline: Z score = .54
• High Score: Z score = 2.38 (significant)
• Percent increase: 33% with a Z score of 2.47 (significant)

The Psychic Reward test results listed above were documented in research papers:

• Vaughan, A., & Houck, J. (1993). A “success” test of precognition and attitude toward the future. Journal of the Society for Psychical Research, 59(833), 259-268.
• Vaughan, A., & Houck, J. (2000). Intuition training software: A second pilot study. Journal of the Society for Psychical Research, 64(3), 177-184

Other Training Scores

MUFON Field Investigator Trainee Examination – 91%

Exploratory

In April 1998, a colleague and investor asked Dr. Smith to come up with a novel method to predict stock market changes, specifically the Dow Jones. As Dr. Smith was then currently using a Random Number Generator (RNG) in her doctoral research, she decided to use this as her measuring instrument. The RNG puts out strings of electronic ones and zeros, in a random order, that accumulate over time to an average output. Any deviation from this average output must be due to something impinging on the data stream of ones and zeros. Data is usually collected in a random order to exclude any existing biases within the data stream. An intent is usually written prior to data collection i.e. to produce more ones (high output); to produce more zeros (low output); or to produce a baseline. The intent, for this experiment was to allow the RNG to trace a random walk that would approximate the random walk of the stock market, over the next three “quarters”.

The intention was written prior to the collection of data and the RNG allowed to run for a specified period. This was done for all three quarters. The data was then divided, into three monthly periods and an analysis of the data made i.e. “Data rises rapidly over the first month, to a plateau over the following month, only to fall to below its starting point in the third month.” The three analyses and raw data were sent to the colleague.

A stock market analyst tracked the predictions against the actual Dow Jones outcomes. For the first quarter there was a strong correspondence between the predictions and actual outcomes. The correspondences became weaker during the second quarter and were off track by the end of the third quarter.