The evidence was
always there.
AI made it count.

The most consequential dataset in consciousness science, systematically evaluated for the first time with a locked, mechanism-neutral medical-evidentiary scoring protocol.

5,000+ NDE accounts
4 AI models
0–100 Signal scale
p < 10−7 Significance threshold

Five steps from raw account to inspectable case profile.

Hover any panel to read what's happening at that stage of the locked, mechanism-neutral scoring pipeline.

Five-part infographic describing NDERF accounts, intake system, AI scoring pipeline, medical-evidentiary output, and the overall methodology claim.
1

NDE Accounts

Self-reports are treated as medical narrative data, not as automatic proof of any mechanism.

2

Structured Intake

The questionnaire captures event context, observations, timing claims, and phenomenological detail.

3

Locked AI Scoring

Advanced reasoning models apply the same multi-stage prompt to every selected case.

4

Case Profiles

Outputs preserve uncertainty through claim-level fields and a case-level headline signal score.

5

Cross-Model Method

Agreement and drift can be measured across model families, prompt versions, and future runs.

Example output language

From "dossiers" to structured case profiles.

"Case profile" keeps the clinical and evidentiary tone without implying a legal file or a formal physician-authored case report. The site can use this public term while the underlying schema remains precise and auditable.

Case #7572 Cardiac arrest
"I watched them apply the paddles. I counted three shocks."
CPR observed Defibrillation Personnel identified
Signal Score 78 / 100

Standards-aware, mechanism-neutral

The claim is methodological before it is statistical.

The scoring instrument does not infer survival, nonlocal perception, anti-materialism, or metaphysical truth. It asks a narrower medical-evidentiary question: how strongly does a report suggest organized conscious experience during a medically bounded interval in which ordinary waking consciousness would be unexpected?

Separate the claims

Event verification, content verification, timing certainty, and medical plausibility remain distinct.

Red-team the ordinary

Prior knowledge, inference, post-event discussion, media tropes, and memory reconstruction are scored explicitly.

Compare model runs

A locked prompt creates an auditable basis for convergence, disagreement, and calibration over time.