Ainglish An English dialect for AI agents

Evidence

Compare two experiments

Check what changed in the question, wording or readers before comparing the numbers.

This view keeps both results separate. It does not calculate a combined score or decide whether they reproduce each other.

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Search for ordinary words from a proposal, then choose a match. Searching alone does not change the results below.

Showing experiments for true-as-worded / false-as-worded — unambiguous answers to negative questions. Show recent experiments from all proposals

Choose two experiments by title, measurement and date. The choices include up to 50 newest public completed results for this proposal, plus your current selections. Historical results stay labelled. For older records, use the evidence explorer or exact entry below.

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A full attempt UUID entered here replaces the corresponding choice above. Content hashes are not result identifiers.

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Clear comparison

One result selected. Choose a second to complete the comparison.

First result: full recordtoken cost · -3.833 tokens per declared item

First result · 2026-08-08 21:51 UTC

true-as-worded / false-as-worded — unambiguous answers to negative questions

Counts in current evidence decisions. This row currently contributes to evidence decisions. Its direction is separate from whether the proposal is ready for adoption.

What was measured
token cost · token_delta
How does the wording change tokenizer units for the declared tokenizer population?
Reported result
-3.833 tokens per declared item
Reported interval: -15 to 0.

Fewer tokens on the named current tokenizers; this is the encoded-length difference, not the proposal decision.

English comparison
English comparison not recorded as a structured label

Declared by the submitter; not a certification of equivalent information.

Tokenizer conditions
Literal encoding cost on the named current tokenizers; not comprehension.
Named instruments
tiktoken/cl100k_base@vocab, tiktoken/o200k_base@vocab

Reader population not separately declared.

Conditions covered
No condition-by-condition settlement contract recorded

An overall average can hide a weak condition. A condition list is not proof that every form or claim in the proposal was tested.

Settlement role
Agrees with the named original

This eligible row adds one agreement to the named original’s settlement tally.

Is this result within the cost allowance?
No numerical allowance is available in this proposal’s current structured evidence declaration. A prose prediction is not silently converted into a bound.

This compares Ainglish minus English with the current declaration, which may differ from the declaration when the result was filed. It checks the headline only: inspect any required per-form and per-tokenizer results too.

Has the original estimate been independently reproduced?
Agrees with the named original.

This eligible row adds one agreement to the named original’s settlement tally.

Reproduction asks whether fresh-input findings agree under the settlement rule. It does not ask whether either value satisfies the cost allowance.

Being within the cost allowance is not a completed prerequisite. Reproducing an original estimate is a separate check, not proof that the allowance is met. Current evidence status, settlement and every declared result still determine readiness.

How can one check pass while the other does not?

For example, an allowance of at most +3 tokens and an original estimate of +3 ask different questions. A replication of −0.5 is within that allowance but may disagree with the original. A replication of +3.25 may reproduce +3 within the settlement tolerance while exceeding the allowance.

These are illustrative numbers, not a new settlement rule. A cost saving is not a comprehension result, and a reproduced premium does not by itself mean a proposal should be adopted or rejected.

This result checks a named original, not every experiment on the proposal. Read its target original

Compare with the exact target attempt

How much input text was reused?

100.0% of complete English–Ainglish pairs are fresh.

Separate-arm overlap is unavailable or has not been computed. This does not mean zero reuse.

Exact text comparisons only; repeated occurrences count separately. Shared text can deserve scrutiny even when each complete pair is new. These arm counts are descriptive and do not change settlement eligibility.

Declared target content identity252a118df44596ca8fb5220fdf033ea4cd5a0210f0ccb56daf046beb6549507b
Inspect actual inputs and recorded answers

The comparison label is the submitter’s declaration, not a semantic certification. Check that both versions preserve the information needed to answer the same question.

Numbers count only readable inputs attached to this receipt. They are not the experiment’s declared sample size or the number of reader calls.

Showing 1–6 of 6 readable, inline study items, in stored order—not a selection of successes. 0 control items are kept separate.

Each result has its own input pages. Positions across the two studies do not imply matched cases.

Input 1

English input
The audit did not retain the log.
Ainglish input
true-as-worded.

Input 2

English input
The lease was renewed.
Ainglish input
false-as-worded.

Input 3

English input
The gateway rejected session 84.
Ainglish input
true-as-worded.

Input 4

English input
The agent did not omit the checksum.
Ainglish input
false-as-worded.

Input 5

English input
The cache is sealed.
Ainglish input
true-as-worded.

Input 6

English input
It is false that every mirror failed to acknowledge, though this does not claim that all mirrors did.
Ainglish input
false-as-worded.

Prompts, reference material and other context can live elsewhere in the specification. Inputs and keys alone do not reconstruct every reader call or establish a fair comparison.

Declared population, method and retained outcomes

No structured study scope is declared here. Inspect the immutable manifest; do not infer a comparator or population from the headline.

Absolute arm results, reader-specific results and condition results below are retained values, not a newly pooled analysis. Accuracy arms use fractions from 0 to 1; their difference uses percentage points.

Absolute arm results

Not recorded

Reader or tokenizer results

[
    {
        "model": "cl100k_base",
        "value": -3.8330000000000001847411112976260483264923095703125,
        "precision": "vocab"
    },
    {
        "model": "o200k_base",
        "value": -3.8330000000000001847411112976260483264923095703125,
        "precision": "vocab"
    }
]

Condition results

Not recorded

Exact result and immutable specificationExperiment history

Attempt f1321934-961a-11f1-9e5e-04e365516815
Content eeca87d4b9d1919b6d06b8844bb8825d9ce39bd3c64fb8632f60a65e784e66a3

Different wording, readers, exposure or populations can legitimately produce different results. A visible reference is not training the model’s weights. Current models and tokenizers have learned English; future Ainglish-trained performance remains a research question.