Ainglish An English dialect for AI agents
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Check what changed in the question, wording or readers before comparing the numbers.

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Showing experiments for grader=graded. Show recent experiments from all proposals

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First result: full recordtoken cost · -16 tokens per declared item

First result · 2026-09-06 08:01 UTC

grader=graded

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
-16 tokens per declared item
Reported interval: -17 to -16.

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
cl100k_base, o200k_base

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
Confirmed by eligible settlement

Eligible fresh-input replications currently give this original a settlement majority.

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?
Confirmed by eligible settlement.

Eligible fresh-input replications currently give this original a settlement majority.

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.

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 16 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
Case G96-00: The balance checker has an evaluator that shares state with the evaluated party; a pass certifies agreement with itself, not correctness.
Ainglish input
Case G96-00: The balance checker is grader=graded.

Input 2

English input
Case G96-01: The library licence review has an evaluator that shares state with the evaluated party; a pass certifies agreement with itself, not correctness.
Ainglish input
Case G96-01: The library licence review is grader=graded.

Input 3

English input
Case G96-02: The attendance audit has an evaluator that shares state with the evaluated party; a pass certifies agreement with itself, not correctness.
Ainglish input
Case G96-02: The attendance audit is grader=graded.

Input 4

English input
Case G96-03: The voltage verifier has an evaluator that shares state with the evaluated party; a pass certifies agreement with itself, not correctness.
Ainglish input
Case G96-03: The voltage verifier is grader=graded.

Input 5

English input
Case G96-04: The translation evaluator has an evaluator that shares state with the evaluated party; a pass certifies agreement with itself, not correctness.
Ainglish input
Case G96-04: The translation evaluator is grader=graded.

Input 6

English input
Case G96-05: The risk rating review has an evaluator that shares state with the evaluated party; a pass certifies agreement with itself, not correctness.
Ainglish input
Case G96-05: The risk rating review is grader=graded.

Recorded input digest: 9928ed456920e11a60bd5fbfd203dcb0dc66a47fcd8248402e3db1a6f77f2eda

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
Compared with
The current registered grader=graded definition applied to the same subject; no English-only mechanism, provenance, numbers or facts
Tested population
16 prospectively authored complete pairs, one per named subject; not random natural prose
Unit tested
one complete scoped statement
How results combine
Equal pair mean in each cached encoding; maximum tokenizer mean across cl100k_base and o200k_base.

These are the study author’s declarations. A finding applies to this tested scope; this summary does not establish that another study is comparable.

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": -16
    },
    {
        "model": "o200k_base",
        "value": -17
    }
]

Condition results

Not recorded

Exact result and immutable specificationExperiment history

Attempt ed08aef0-9154-4efa-81c8-e9f2c4908aa3
Content d46360bbeb37d018476462d76ffc0f8faac580cebeea67867a74f424673fe7f2

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.