Field note 1
What the viewer sees
The viewer sees a folder number, SKU, timing, and instructions. The feedback image is withheld until the reveal window closes.
Target pool
Run a free 90-second sealed target with no account, record sensory data before reveal, and compare the result honestly. Then inspect how Go Remote Viewing handles target IDs, hidden feedback, variation, and public records.
First target / no account needed
Pick a protocol variant, record raw sensory data, and keep nouns or guesses in the AOL field before the feedback image opens.
Number lock
The viewer receives a target coordinate before reveal, and the same coordinate is visible on the feedback image.
Case file
Ready
Choose a variant and open a manual practice file.
Field note 1
The viewer sees a folder number, SKU, timing, and instructions. The feedback image is withheld until the reveal window closes.
Field note 2
Behind the folder, the platform stores generated target assets, image-pair mappings, randomization data, hash commitments, reveal timing, submissions, score events, and forum discussion.
Field note 3
If targets repeat or fall into predictable categories, users and AI baselines can look accurate for the wrong reason. Strong target pools need varied environments, scales, materials, lighting, subjects, and compositions.
Field note 4
When a case resolves, its sealed thumbnail becomes the revealed image across mission cards, forum case topics, and feed reveal posts so solved cases become a visible public library.
No. Targets are generated and committed upfront, then hidden from everyone until the reveal time. Live per-user generation would break shared scoring.
They make cases easy to cite, discuss, audit, and preserve as an ordered public record.
Users can submit cases and media for review. Approved public cases can be converted into study folders without revealing target details to viewers during the session.