Ainglish An English dialect for AI agents

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First result: full recordcomprehension accuracy · -6.5887 percentage points

First result · 2026-09-06 11:31 UTC

prob / odds-for / odds-against — is a risk a share or a ratio, and which side comes first?

Not yet counting in evidence decisions. This row remains available for assessment, but does not currently carry a counting evidence result.

What was measured
comprehension accuracy · comprehension_accuracy_delta
How does the wording change correct answers from the declared reader panel?
Reported result
-6.5887 percentage points
Reported interval: -13.5074 to 1.0726.

The value is neutral or does not resolve the registered direction.

English comparison
Complete, careful English

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

Identical contextual facts in both arms; direct complete English for the question asked. Scope and omitted dimensions are explicit in DESIGN.md.

Reader exposure
Reader exposure not recorded as a structured label
Named instruments
mistral-small3.2-24b-opaque-choice-q4_k_m@q4_k_m, gemma3-12b-opaque-choice-q4_k_m@q4_k_m

Reader population not separately declared.

Conditions covered
Separate outcomes retained for all 15 declared conditions

prob:payout, prob:calibration, prob:frequency, prob:causation, prob:rounding, odds-for:payout, odds-for:calibration, odds-for:frequency, odds-for:causation, odds-for:rounding, odds-against:payout, odds-against:calibration, odds-against:frequency, odds-against:causation, odds-against:rounding

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
Disputed

Eligible replications disagree and this original does not hold a settlement majority.

How often did each version lead to the right answer?

English comparison
90.33%
90.33%
Ainglish version
83.75%
83.75%

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: -13.5074 to 1.0726 percentage points.

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

At least one declared condition is resolution-limited. The overall interval does not settle every condition.

Item-selection sensitivity warning. At least one reported reduced-item check changed direction or fell outside the full-item interval. Keep this warning with the score: the headline interval alone does not resolve sensitivity to which cases were included.

Real cases: 120 · 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
prob:payout34.55 Not recorded 45.45%80.00%
prob:calibration0 Not recorded 100.00%100.00%
prob:frequency0 Not recorded 100.00%100.00%
prob:causation-25 Not recorded 87.50%62.50%
prob:rounding0 Not recorded 100.00%100.00%
odds-for:payout-50 Not recorded 100.00%50.00%
odds-for:calibration-11.11 Not recorded 100.00%88.89%
odds-for:frequency11.11 Not recorded 88.89%100.00%
odds-for:causation-30.77 Not recorded 100.00%69.23%
odds-for:rounding0 Not recorded 100.00%100.00%
odds-against:payout-15.87 Not recorded 71.43%55.56%
odds-against:calibration0 Not recorded 87.50%87.50%
odds-against:frequency16.67 Not recorded 83.33%100.00%
odds-against:causation-37.5 Not recorded 100.00%62.50%
odds-against:rounding9.09 Not recorded 90.91%100.00%

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: 14046a8994a73e8120eaec31f4d24244c6c7b206de0fa51d96162d55312f5333. 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": 0.9032999999999999918287585387588478624820709228515625,
    "ainglish": 0.83750000000000002220446049250313080847263336181640625,
    "chance": 0.5
}

Reader or tokenizer results

[
    {
        "model": "mistral-small3.2-24b-opaque-choice-q4_k_m",
        "value": -5.9047000000000000596855898038484156131744384765625,
        "precision": "q4_k_m"
    },
    {
        "model": "gemma3-12b-opaque-choice-q4_k_m",
        "value": -6.06400000000000005684341886080801486968994140625,
        "precision": "q4_k_m"
    }
]

Condition results

[
    {
        "id": "prob:payout",
        "weight": 1,
        "share": 0.06666666666666666574148081281236954964697360992431640625,
        "value": 34.5499999999999971578290569595992565155029296875,
        "value_lo": null,
        "value_hi": null,
        "arms": {
            "english": 0.45450000000000001509903313490212894976139068603515625,
            "ainglish": 0.8000000000000000444089209850062616169452667236328125,
            "chance": 0.5
        },
        "resolution_bound": "resolvable"
    },
    {
        "id": "prob:calibration",
        "weight": 1,
        "share": 0.06666666666666666574148081281236954964697360992431640625,
        "value": 0,
        "value_lo": null,
        "value_hi": null,
        "arms": {
            "english": 1,
            "ainglish": 1,
            "chance": 0.5
        },
        "resolution_bound": "ceiling"
    },
    {
        "id": "prob:frequency",
        "weight": 1,
        "share": 0.06666666666666666574148081281236954964697360992431640625,
        "value": 0,
        "value_lo": null,
        "value_hi": null,
        "arms": {
            "english": 1,
            "ainglish": 1,
            "chance": 0.5
        },
        "resolution_bound": "ceiling"
    },
    {
        "id": "prob:causation",
        "weight": 1,
        "share": 0.06666666666666666574148081281236954964697360992431640625,
        "value": -25,
        "value_lo": null,
        "value_hi": null,
        "arms": {
            "english": 0.875,
            "ainglish": 0.625,
            "chance": 0.5
        },
        "resolution_bound": "resolvable"
    },
    {
        "id": "prob:rounding",
        "weight": 1,
        "share": 0.06666666666666666574148081281236954964697360992431640625,
        "value": 0,
        "value_lo": null,
        "value_hi": null,
        "arms": {
            "english": 1,
            "ainglish": 1,
            "chance": 0.5
        },
        "resolution_bound": "ceiling"
    },
    {
        "id": "odds-for:payout",
        "weight": 1,
        "share": 0.06666666666666666574148081281236954964697360992431640625,
        "value": -50,
        "value_lo": null,
        "value_hi": null,
        "arms": {
            "english": 1,
            "ainglish": 0.5,
            "chance": 0.5
        },
        "resolution_bound": "resolvable"
    },
    {
        "id": "odds-for:calibration",
        "weight": 1,
        "share": 0.06666666666666666574148081281236954964697360992431640625,
        "value": -11.1099999999999994315658113919198513031005859375,
        "value_lo": null,
        "value_hi": null,
        "arms": {
            "english": 1,
            "ainglish": 0.888900000000000023447910280083306133747100830078125,
            "chance": 0.5
        },
        "resolution_bound": "resolvable"
    },
    {
        "id": "odds-for:frequency",
        "weight": 1,
        "share": 0.06666666666666666574148081281236954964697360992431640625,
        "value": 11.1099999999999994315658113919198513031005859375,
        "value_lo": null,
        "value_hi": null,
        "arms": {
            "english": 0.888900000000000023447910280083306133747100830078125,
            "ainglish": 1,
            "chance": 0.5
        },
        "resolution_bound": "resolvable"
    },
    {
        "id": "odds-for:causation",
        "weight": 1,
        "share": 0.06666666666666666574148081281236954964697360992431640625,
        "value": -30.769999999999999573674358543939888477325439453125,
        "value_lo": null,
        "value_hi": null,
        "arms": {
            "english": 1,
            "ainglish": 0.69230000000000002646771690706373192369937896728515625,
            "chance": 0.5
        },
        "resolution_bound": "resolvable"
    },
    {
        "id": "odds-for:rounding",
        "weight": 1,
        "share": 0.06666666666666666574148081281236954964697360992431640625,
        "value": 0,
        "value_lo": null,
        "value_hi": null,
        "arms": {
            "english": 1,
            "ainglish": 1,
            "chance": 0.5
        },
        "resolution_bound": "ceiling"
    },
    {
        "id": "odds-against:payout",
        "weight": 1,
        "share": 0.06666666666666666574148081281236954964697360992431640625,
        "value": -15.8699999999999992184029906638897955417633056640625,
        "value_lo": null,
        "value_hi": null,
        "arms": {
            "english": 0.71430000000000004600764214046648703515529632568359375,
            "ainglish": 0.55559999999999998276933865781757049262523651123046875,
            "chance": 0.5
        },
        "resolution_bound": "resolvable"
    },
    {
        "id": "odds-against:calibration",
        "weight": 1,
        "share": 0.06666666666666666574148081281236954964697360992431640625,
        "value": 0,
        "value_lo": null,
        "value_hi": null,
        "arms": {
            "english": 0.875,
            "ainglish": 0.875,
            "chance": 0.5
        },
        "resolution_bound": "resolvable"
    },
    {
        "id": "odds-against:frequency",
        "weight": 1,
        "share": 0.06666666666666666574148081281236954964697360992431640625,
        "value": 16.6700000000000017053025658242404460906982421875,
        "value_lo": null,
        "value_hi": null,
        "arms": {
            "english": 0.83330000000000004067857162226573564112186431884765625,
            "ainglish": 1,
            "chance": 0.5
        },
        "resolution_bound": "resolvable"
    },
    {
        "id": "odds-against:causation",
        "weight": 1,
        "share": 0.06666666666666666574148081281236954964697360992431640625,
        "value": -37.5,
        "value_lo": null,
        "value_hi": null,
        "arms": {
            "english": 1,
            "ainglish": 0.625,
            "chance": 0.5
        },
        "resolution_bound": "resolvable"
    },
    {
        "id": "odds-against:rounding",
        "weight": 1,
        "share": 0.06666666666666666574148081281236954964697360992431640625,
        "value": 9.089999999999999857891452847979962825775146484375,
        "value_lo": null,
        "value_hi": null,
        "arms": {
            "english": 0.909100000000000019184653865522705018520355224609375,
            "ainglish": 1,
            "chance": 0.5
        },
        "resolution_bound": "ceiling"
    }
]

Exact result and immutable specificationExperiment history

Attempt 638d2aab-f063-48c2-bb8f-7d27ab7af3b4
Content f270857d598a65b32d12b172773219e48e5c71950dc0dd4940f8bfddd081b4ee

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.