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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.

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

Use an exact experiment identifier instead

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

Clear comparison

Compare the essentials

Read each question across both results. A matching description is not proof that the studies are scientifically comparable.

QuestionFirst resultSecond result
Which proposal?mean-of / median-of — which ‘average’ did you report?2026-09-03 09:24 UTCmean-of / median-of — which ‘average’ did you report?2026-09-05 14:03 UTC
What was measured?token costHow does the wording change tokenizer units for the declared tokenizer population?token costHow does the wording change tokenizer units for the declared tokenizer population?
What was the result?-7.0625 tokens per declared itemReported interval: -8.875 to -7.0625Counts in current evidence decisions-7.5 tokens per declared itemReported interval: -9.25 to -7.5Counts in current evidence decisions
Compared with what?English comparison not recorded as a structured labelCurrent tokenizer cost, not comprehensionEnglish comparison not recorded as a structured labelCurrent tokenizer cost, not comprehension
Independently settled?Confirmed by eligible settlementEligible fresh-input replications currently give this original a settlement majority.Agrees with the named originalThis eligible row adds one agreement to the named original’s settlement tally.

Inspect first resultInspect second result

What differs in the declared methods?

These are literal recorded values, not a compatibility test. Matching declarations do not prove equivalent inputs or fair scoring. A missing structured field may be described elsewhere in the immutable specification.

What was measured · Same recorded value
First result
token_delta
Second result
token_delta
English comparison declarations · Not recorded on either side
First result
Not recorded in this structured field
Second result
Not recorded in this structured field
Tested population · Same recorded value
First result
32 frozen wholly fresh assertions over 16 exact finite population references, balanced 16 mean-of and 16 median-of
Second result
32 frozen wholly fresh assertions over 16 exact finite population references, balanced 16 mean-of and 16 median-of
Unit tested · Same recorded value
First result
complete statistic assertion with exact finite population reference
Second result
complete statistic assertion with exact finite population reference
Named instruments (including order) · Same recorded value
First result
[
    "cl100k_base",
    "o200k_base",
    "p50k_base"
]
Second result
[
    "cl100k_base",
    "o200k_base",
    "p50k_base"
]
Reader exposure · Not recorded on either side
First result
Not recorded in this structured field
Second result
Not recorded in this structured field
Exposure window · Not recorded on either side
First result
Not recorded in this structured field
Second result
Not recorded in this structured field
How results combine · Same recorded value
First result
{
    "reducer": "least_favourable",
    "rule": "equal item mean within each form stratum, equal weight across the two form strata, then maximum tokenizer mean"
}
Second result
{
    "reducer": "least_favourable",
    "rule": "equal item mean within each form stratum, equal weight across the two form strata, then maximum tokenizer mean"
}
Scoring declaration · Not recorded on either side
First result
Not recorded in this structured field
Second result
Not recorded in this structured field
Conditions (including order) · Same recorded value
First result
[
    {
        "id": "mean-of",
        "weight": 1
    },
    {
        "id": "median-of",
        "weight": 1
    }
]
Second result
[
    {
        "id": "mean-of",
        "weight": 1
    },
    {
        "id": "median-of",
        "weight": 1
    }
]
First result: full recordtoken cost · -7.0625 tokens per declared item

First result · 2026-09-03 09:24 UTC

mean-of / median-of — which ‘average’ did you report?

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
-7.0625 tokens per declared item
Reported interval: -8.875 to -7.0625.

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, p50k_base

Reader population not separately declared.

Conditions covered
Separate outcomes retained for all 2 declared conditions

mean-of, median-of

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?
This headline is within the allowance. The reported difference is -7.0625 tokens; the current declaration allows at most 0 tokens.

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.

Does the overall result hide differences between conditions?

Every stored condition, without new pooling. Differences and intervals use tokens. Condition names come from the frozen experiment.
ConditionReported differenceReported interval
mean-of-9.5625 Not recorded
median-of-4.5625 Not recorded

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

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 32 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 · mean-01

English input
The unweighted arithmetic mean of every numeric observation in the exact finite population packet-loss-ppm@edge-west-2026w35-v3 is 18 ppm.
Ainglish input
mean-of(packet-loss-ppm@edge-west-2026w35-v3) = 18 ppm.
Condition
mean-of

Input 2 · median-01

English input
The median of every numeric observation in the exact finite population packet-loss-ppm@edge-west-2026w35-v3 is 7 ppm.
Ainglish input
median-of(packet-loss-ppm@edge-west-2026w35-v3) = 7 ppm.
Condition
median-of

Input 3 · mean-02

English input
The unweighted arithmetic mean of every numeric observation in the exact finite population response-ms@checkout-canary-2026-09-01-v4 is 184 ms.
Ainglish input
mean-of(response-ms@checkout-canary-2026-09-01-v4) = 184 ms.
Condition
mean-of

Input 4 · median-02

English input
The median of every numeric observation in the exact finite population response-ms@checkout-canary-2026-09-01-v4 is 61 ms.
Ainglish input
median-of(response-ms@checkout-canary-2026-09-01-v4) = 61 ms.
Condition
median-of

Input 5 · mean-03

English input
The unweighted arithmetic mean of every numeric observation in the exact finite population queue-wait-s@warehouse-night-2026-08-v2 is 93 s.
Ainglish input
mean-of(queue-wait-s@warehouse-night-2026-08-v2) = 93 s.
Condition
mean-of

Input 6 · median-03

English input
The median of every numeric observation in the exact finite population queue-wait-s@warehouse-night-2026-08-v2 is 44 s.
Ainglish input
median-of(queue-wait-s@warehouse-night-2026-08-v2) = 44 s.
Condition
median-of

Recorded input digest: 22833285115fe0958ea99e0efd88257e3bc3de872a9f278a5f1a3a95fd65c618

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
marked mean-of or median-of assertion versus its complete careful-English statistic and population-reference assertion
Tested population
32 frozen wholly fresh assertions over 16 exact finite population references, balanced 16 mean-of and 16 median-of
Unit tested
complete statistic assertion with exact finite population reference
How results combine
equal item mean within each form stratum, equal weight across the two form strata, then maximum tokenizer mean

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": -8.8125
    },
    {
        "model": "o200k_base",
        "value": -8.875
    },
    {
        "model": "p50k_base",
        "value": -7.0625
    }
]

Condition results

[
    {
        "id": "mean-of",
        "weight": 1,
        "share": 0.5,
        "value": -9.5625,
        "value_lo": null,
        "value_hi": null,
        "arms": null,
        "resolution_bound": "not_applicable"
    },
    {
        "id": "median-of",
        "weight": 1,
        "share": 0.5,
        "value": -4.5625,
        "value_lo": null,
        "value_hi": null,
        "arms": null,
        "resolution_bound": "not_applicable"
    }
]

Exact result and immutable specificationExperiment history

Attempt 340d91cb-7aed-424c-a945-3612126de726
Content d00a55dadec550f4a7f30a8c2e40b5a49a5f0a6c62a9b035df305b3dc2e5c2ba

Second result: full recordtoken cost · -7.5 tokens per declared item

Second result · 2026-09-05 14:03 UTC

mean-of / median-of — which ‘average’ did you report?

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
-7.5 tokens per declared item
Reported interval: -9.25 to -7.5.

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, p50k_base

Reader population not separately declared.

Conditions covered
Separate outcomes retained for all 2 declared conditions

mean-of, median-of

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?
This headline is within the allowance. The reported difference is -7.5 tokens; the current declaration allows at most 0 tokens.

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 replication reports -7.5 tokens; the named original reported -7.0625.

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

Every declared condition must agree. Overlapping overall intervals alone do not confirm this original.

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 identityd00a55dadec550f4a7f30a8c2e40b5a49a5f0a6c62a9b035df305b3dc2e5c2ba

Does the overall result hide differences between conditions?

Every stored condition, without new pooling. Differences and intervals use tokens. Condition names come from the frozen experiment.
ConditionReported differenceReported interval
mean-of-10 Not recorded
median-of-5 Not recorded

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

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
The unweighted arithmetic mean of every numeric observation in the exact finite population cpu-pct@edge-east-2026w36-v1 is 62 percent.
Ainglish input
mean-of(cpu-pct@edge-east-2026w36-v1) = 62 percent.
Condition
mean-of

Input 2

English input
The median of every numeric observation in the exact finite population cpu-pct@edge-east-2026w36-v1 is 58 percent.
Ainglish input
median-of(cpu-pct@edge-east-2026w36-v1) = 58 percent.
Condition
median-of

Input 3

English input
The unweighted arithmetic mean of every numeric observation in the exact finite population mem-mb@central-2026w36-v2 is 4120 MB.
Ainglish input
mean-of(mem-mb@central-2026w36-v2) = 4120 MB.
Condition
mean-of

Input 4

English input
The median of every numeric observation in the exact finite population mem-mb@central-2026w36-v2 is 4096 MB.
Ainglish input
median-of(mem-mb@central-2026w36-v2) = 4096 MB.
Condition
median-of

Input 5

English input
The unweighted arithmetic mean of every numeric observation in the exact finite population disk-iops@edge-west-2026w36-v1 is 8800 IOPS.
Ainglish input
mean-of(disk-iops@edge-west-2026w36-v1) = 8800 IOPS.
Condition
mean-of

Input 6

English input
The median of every numeric observation in the exact finite population disk-iops@edge-west-2026w36-v1 is 8450 IOPS.
Ainglish input
median-of(disk-iops@edge-west-2026w36-v1) = 8450 IOPS.
Condition
median-of

Recorded input digest: 8f26e5ff9fb228f901ce5d967f6ac2c35eae44adf65895fcfe5fe8853731bdd2

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
marked mean-of or median-of assertion versus its complete careful-English statistic and population-reference assertion
Tested population
32 frozen wholly fresh assertions over 16 exact finite population references, balanced 16 mean-of and 16 median-of
Unit tested
complete statistic assertion with exact finite population reference
How results combine
equal item mean within each form stratum, equal weight across the two form strata, then maximum tokenizer mean

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": -9.25
    },
    {
        "model": "o200k_base",
        "value": -9.25
    },
    {
        "model": "p50k_base",
        "value": -7.5
    }
]

Condition results

[
    {
        "id": "mean-of",
        "weight": 1,
        "share": 0.5,
        "value": -10,
        "value_lo": null,
        "value_hi": null,
        "arms": null,
        "resolution_bound": "not_applicable"
    },
    {
        "id": "median-of",
        "weight": 1,
        "share": 0.5,
        "value": -5,
        "value_lo": null,
        "value_hi": null,
        "arms": null,
        "resolution_bound": "not_applicable"
    }
]

Exact result and immutable specificationExperiment history

Attempt 12adbc1c-18d8-4d42-9f44-1bad0b6d6eb1
Content 6ae4b8af604365ad032e697ec658e640bc4f1b5ee5ee4ae1b691c32095ac7106

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.