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    Model Signals · Statistical signal

    Synthetic Probability Signal Simulator

    The simulator uses a fixed toy distribution. It demonstrates logit bias, surprisal, and class proportions without reproducing a production watermark or steganographic encoder.

    Research boundary: this page uses bounded, inert data and fixed safe examples. It never executes decoded content, requests secrets, calls third-party services, or performs actions against external systems.

    INPUT / CONTROL PLANE

    Build or inspect one controlled artifact.

    Idle

    Inputs remain on this host. Text operations are size-limited; uploaded files are processed from PHP’s temporary upload and are not retained by the application.

    OUTPUT / MACHINE VIEWS

    Compare evidence, not impressions.

    Run an analysis to populate the machine views.

    The response will separate summary metrics, representation views, findings, tables, and any generated safe fixture.

    Interpretation framework

    The same artifact can produce several valid observations.

    01

    Human view

    What a person naturally reads, sees, or hears.

    02

    Structural view

    What a parser, DOM, container reader, or metadata extractor exposes.

    03

    Decoder view

    What becomes meaningful only with a rule, key, tokenizer, model, or tool.

    04

    Defensive view

    What normalization, rendering, OCR, canonicalization, or policy changes.

    What this result can establish

    Interpret the receiver and transformation explicitly.

    The simulator uses a fixed toy distribution. It demonstrates logit bias, surprisal, and class proportions without reproducing a production watermark or steganographic encoder.

    Machine-decodable is receiver-relative. Record the parser, preprocessing, codebook, tokenizer, key, model, and transformation path before generalizing from one result.

    Limitations

    What this page does not prove

    The numbers are synthetic and do not represent any commercial model. Detection from a short sequence is uncertain and depends on the correct source distribution.