Invitation App / Deep dive 01

Five Research
Modes

Five different ways to observe a session without pretending that any single output explains itself. Every mode contributes to the same timestamped evidence trail.

Explore each mode ↓

Different signals, one standard

A mode records.
It does not declare.

Each research mode looks at a different kind of possible event: a displayed word, a response window, a phonetic fragment, mapped visual geometry, or the surrounding session record.

The public can understand what each mode does, what the participant sees, and what evidence is preserved. Exact thresholds, internal weighting, dictionaries, selection logic, and source code remain protected.

Shared rule: output becomes a reviewable event—not automatic proof, not a guaranteed message, and not a conclusion about its source.

Inside a submitted session

What we learn from the record

Open an evidence type to see the observations, checks, and conclusions in a session review. These examples use the October 5 export and summaries already published on this site. Contributor identities and private files are omitted.

Reviewed export · October 5, 2026

A 74-minute Free Word session

Paranormal Invites Prototype 1.7, Build 8 recorded one Room A session on an Android phone. The review compared its word events, raw sensor readings, calibration history, movement checks, and ARI audit.

Word outputs
26
Distinct words
25
Field changes suppressed
4
Raw sensor samples
17,784

What the log shows

  • The first room baseline was rejected after detected phone movement and unstable magnetic readings. The automatic retry completed and locked a baseline before any word was released.
  • Each of the 26 word records includes a qualifying EMF event. The records label timer triggering and network influence as absent.
  • ARI passed the recorded event checks for all 26 outputs. It uses the same phone sensors, so these checks are not independent-device corroboration.
  • Four abrupt single-channel magnetic-field transitions were suppressed. The reference was also reset after detected movement; no released word was marked movement-contaminated.
  • The device had no ambient-temperature sensor. This export contained no question cycles, phonetic events, EVP candidates, SLS captures, recorded media, or participant notes.
Read the 26 captured words

CRAB · DIFFICULT · BLUE · PLEASANT · AFFLICT · APPROVE · DEFEAT · DISLIKE · BLUNT · BLIND · REFINEMENT · ASPIRATE · BLIND · BRINGING · COLLECTIVELY · FENCE · ENTREATY · PLANK · MOLDING · VASSAL · OPPOSITION · EVIDENCE · GRANITE · SPRIGHTLY · TONGUE · MEASURING.

BLIND appeared twice. A repeated word is documented without assigning it a meaning.

What we check

Whether outputs followed completed calibration, what sensor channel qualified, whether movement or sound was flagged, which changes were suppressed, and whether the record contains independent observations to compare.

Review finding: The export documents EMF-linked word outputs under the app’s recorded rules. It does not establish the cause of the magnetic changes or demonstrate communication. The audit entries describe software decisions, not independent verification of their cause.

01–05 / MODE DETAILS

What each mode contributes

01

Individual word events

Live Word

Open a submitted review example

Live Word presents a word event only after the selected room baseline has completed. The event is placed on the session timeline with the conditions available at that moment.

What the participant does
Starts a session, completes the baseline, opens the invitation, and observes without forcing constant output.
What is preserved
The displayed word, exact event time, active room profile, app build, and surrounding session context.
How it is reviewed
For timing, possible relevance, repetition, nearby sound or motion, and whether a different explanation fits.
What it cannot prove
A word alone cannot identify its source, intent, or whether it represents communication.
02

Defined response windows

Ask a Question

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Ask a Question connects a spoken prompt to a defined observation window. This makes the timing reviewable instead of relying on memory about which output followed which question.

What the participant does
Presses to ask, speaks one clear question, then waits through the visible response period before asking another.
What is preserved
The question event, waiting window, any recorded output, timestamps, and relevant session conditions.
How it is reviewed
By comparing answered and unanswered windows, response timing, context, and repeat trials.
What it cannot prove
An output occurring after a question is a timing correlation; timing alone does not prove a response or speaker.
03

Raw sound fragments

Phonetic

Open a submitted review example

Phonetic mode preserves app-generated syllable sequences for later review. These outputs are not captured speech or EVP recordings. A session with no produced sound may still contain sensor activity below the output threshold, which remains useful for comparison. The mode is intentionally cautious because the human mind can turn ambiguous sound into expected words.

What the participant does
Runs a longer listening session—commonly a controlled ten-minute trial—and avoids announcing interpretations during capture.
What is preserved
Generated fragments, timing, session position, and available microphone and environmental context.
How it is reviewed
Original sound comes first. Possible wording is documented separately and may be compared across independent listeners.
What it cannot prove
An unclear syllable is not converted into a confirmed word merely because it resembles one.
04

Visual geometry mapping

SLS Vision

Open a submitted review example

SLS Vision identifies human-like geometry in the camera view and can preserve a still image or recording when a possible figure is mapped.

What the participant does
Scans deliberately, keeps the scene visible, limits unnecessary camera movement, and records relevant requests or observations.
What is preserved
The original scene, mapping overlay, detection time, available motion context, and user-created capture or recording.
How it is reviewed
Furniture, people, edges, reflections, lighting, camera movement, and repeatability are checked before calling a map unresolved.
What it cannot prove
Human-shaped geometry is not proof of a human—or a spirit. Pose systems can map ordinary objects incorrectly.
05

The context around every event

Session Evidence

Open a submitted review example

Session Evidence is the connecting layer. It gives individual outputs a traceable place inside the larger session rather than presenting them as isolated moments.

What the participant does
Completes the session, adds honest notes, reviews the record, and chooses whether to submit it for research.
What is preserved
Baseline, timestamps, app version, available movement, sound and radio context, outputs, captures, notes, no-response periods, below-threshold sensor context, and end state.
How it is reviewed
Events can be compared across modes to find genuine timing correlation or identify contamination.
What it cannot prove
A complete record improves credibility, but completeness does not determine the cause of an unexplained event.
06 / WORKING TOGETHER

Correlation, not combination tricks

One clock makes comparison possible.

The modes become more useful when independent events align in time under documented conditions.

A word following a question, an SLS map appearing near a separate sensor event, or repeated results under the same controlled setup may deserve closer review. The app still preserves non-aligned events and silent periods so coincidence is not hidden.

1Single output
→
2Context attached
→
3Repeated under control
→
4Independent correlation

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