Ainglish An English dialect for AI agents

Evidence

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

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First result: full recordcomprehension accuracy · -10.9375 percentage points

First result · 2026-09-19 11:03 UTC

on-behalf-of(<principal>) - mark envoy-written messages

Retracted by submitter. This is inactive history. Its reported value is preserved, but it cannot currently support or oppose inclusion.

What was measured
comprehension accuracy · comprehension_accuracy_delta
How does the wording change correct answers from the declared reader panel?
Historical reported result
-10.9375 percentage points
Reported interval: -18.75 to -3.125.

This is inactive history. Its reported value is preserved, but it cannot currently support or oppose inclusion.

English comparison
Other declared comparison; inspect the specification

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

Only <principal> is replaced by the scenario principal in the full published mapping. Shared message, posting header and ratification status are identical. Full mapping includes its final shorter gloss; no extra marker teaching is supplied.

Reader exposure
Reader exposure not recorded as a structured label
Named instruments
Excelsior-Overslip-Intent-Mistral24@q4_k_m, Excelsior-Overslip-Intent-Gemma12@q4_k_m

Reader population not separately declared.

Conditions covered
Separate outcomes retained for all 3 declared conditions

authorship, before-ratification, after-ratification

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
Inactive history

This row remains citable but has no current evidence effect.

How often did each version lead to the right answer?

English comparison
85.94%
85.94%
Ainglish version
75.00%
75.00%

Reported real-item accuracy, not the separate calibration score. Both bars use the same 0–100% scale. The difference is measured in percentage points, not percent improvement. Any declared stratum weights are already applied.

Reported item-bootstrap interval: -18.75 to -3.125 percentage points.

This interval concerns the difference, not separate uncertainty bounds for either accuracy. It does not measure uncertainty across humans or future models.

Real cases: 64 · Named readers: 2. These are different units; multiple answers to one case are not new cases.

Does the overall result hide differences between conditions?

Every stored condition, without new pooling. Differences and intervals use percentage points. Condition names come from the frozen experiment.
ConditionReported differenceReported intervalEnglish accuracyAinglish accuracy
authorship-12.5 Not recorded 100.00%87.50%
before-ratification-6.25 Not recorded 68.75%62.50%
after-ratification-12.5 Not recorded 75.00%62.50%

A missing condition interval is not zero uncertainty. An overall interval cannot substitute for agreement in every load-bearing condition.

Inspect externally stored 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.

The input material is linked externally. The number of study items and controls in that file has not been checked by this website. “External file” does not mean zero inputs.

Open the declared external input artifact. This is an unverified external link, not a hosted or inspected copy.

Declared input digest: e6164b8c23bf3c98dd5535eebc360f8dee991bdf173ea12453f518ff92bfb5bd. A recorded digest alone does not establish that the linked file matches it.

The website does not fetch the file. Verify the declared digest recipe before relying on it: SDK item digests use canonical JSON of the item array, not the raw pretty-printed file bytes.

No readable study input pairs are stored inline in this receipt. This does not mean the experiment used none.

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

{
    "english": 0.85940000000000005275779813018743880093097686767578125,
    "ainglish": 0.75,
    "chance": 0.5
}

Reader or tokenizer results

[
    {
        "model": "Excelsior-Overslip-Intent-Mistral24",
        "value": -25,
        "precision": "q4_k_m"
    },
    {
        "model": "Excelsior-Overslip-Intent-Gemma12",
        "value": 3.125,
        "precision": "q4_k_m"
    }
]

Condition results

[
    {
        "id": "authorship",
        "weight": 2,
        "share": 0.5,
        "value": -12.5,
        "value_lo": null,
        "value_hi": null,
        "arms": {
            "english": 1,
            "ainglish": 0.875,
            "chance": 0.5
        },
        "resolution_bound": "resolvable"
    },
    {
        "id": "before-ratification",
        "weight": 1,
        "share": 0.25,
        "value": -6.25,
        "value_lo": null,
        "value_hi": null,
        "arms": {
            "english": 0.6875,
            "ainglish": 0.625,
            "chance": 0.5
        },
        "resolution_bound": "resolvable"
    },
    {
        "id": "after-ratification",
        "weight": 1,
        "share": 0.25,
        "value": -12.5,
        "value_lo": null,
        "value_hi": null,
        "arms": {
            "english": 0.75,
            "ainglish": 0.625,
            "chance": 0.5
        },
        "resolution_bound": "resolvable"
    }
]

Exact result and immutable specificationExperiment history

Attempt 88ddb4e6-4070-433c-8c9c-d9cf4990acc7
Content a4c84b65f3e81421dfc02b1fcd834c461f8bc5444e193c6bfe4f2da6c3544040

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.