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.

Change the selected experimentsSearch by proposal, select a result or enter an exact identifier

Find experiments by proposal

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.

Question	First result	Second result
Which proposal?	different-from(ref, by=key) / different-across(group, by=key) — what is a ‘different’ choice different from?2026-08-26 14:38 UTC	different-from(ref, by=key) / different-across(group, by=key) — what is a ‘different’ choice different from?2026-08-28 16:06 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?	-0.1875 tokens per declared itemReported interval: -2.65625 to -0.1875Counts in current evidence decisions	-0.1875 tokens per declared itemReported interval: -2.375 to -0.1875Counts in current evidence decisions
Compared with what?	English comparison not recorded as a structured labelCurrent tokenizer cost, not comprehension	English 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 result Inspect 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 · Not recorded on either side

First result

Not recorded in this structured field

Second result

Not recorded in this structured field

Unit tested · Not recorded on either side

First result

Not recorded in this structured field

Second result

Not recorded in this structured field

Named instruments (including order) · Same recorded value

First result

[
    "tiktoken/cl100k_base",
    "tiktoken/o200k_base",
    "tiktoken/p50k_base"
]

Second result

[
    "tiktoken/cl100k_base",
    "tiktoken/o200k_base",
    "tiktoken/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 · Not recorded on either side

First result

Not recorded in this structured field

Second result

Not recorded in this structured field

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) · Not recorded on either side

First result

Not recorded in this structured field

Second result

Not recorded in this structured field

First result: full recordtoken cost · -0.1875 tokens per declared item

First result · 2026-08-26 14:38 UTC

different-from(ref, by=key) / different-across(group, by=key) — what is a ‘different’ choice different from?

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: -0.1875 tokens per declared item
Reported interval: -2.65625 to -0.1875.
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, tiktoken/o200k_base, tiktoken/p50k_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?

This headline is within the allowance. The reported difference is -0.1875 tokens; the current declaration allows at most 2 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.

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

English input: Choice 01: select a model whose model-id is unequal to the reference model's model-id.
Ainglish input: Choice 01: select a model different-from(reference-model, by=model-id).

Input 2

English input: Choice 01: assign a model to every reviewer such that distinct reviewers' selected model-id values are pairwise unequal.
Ainglish input: Choice 01: assign a model to every reviewer different-across(reviewers, by=model-id).

Input 3

English input: Choice 02: select a artifact whose checksum is unequal to the reference artifact's checksum.
Ainglish input: Choice 02: select a artifact different-from(reference-artifact, by=checksum).

Input 4

English input: Choice 02: assign a artifact to every reviewer such that distinct reviewers' selected checksum values are pairwise unequal.
Ainglish input: Choice 02: assign a artifact to every reviewer different-across(reviewers, by=checksum).

Input 5

English input: Choice 03: select a endpoint whose owner is unequal to the reference endpoint's owner.
Ainglish input: Choice 03: select a endpoint different-from(reference-endpoint, by=owner).

Input 6

English input: Choice 03: assign a endpoint to every reviewer such that distinct reviewers' selected owner values are pairwise unequal.
Ainglish input: Choice 03: assign a endpoint to every reviewer different-across(reviewers, by=owner).

Recorded input digest: 9796181083e15212b2dc5a5abb2a1f8ff4f69f59a32bd0f55059df7753ce9959

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": "tiktoken\/cl100k_base",
        "value": -2.1875
    },
    {
        "model": "tiktoken\/o200k_base",
        "value": -2.65625
    },
    {
        "model": "tiktoken\/p50k_base",
        "value": -0.1875
    }
]

Condition results

Not recorded

Exact result and immutable specification Experiment history

Attempt 5cf4ed2f-2c3b-46ef-8722-81b1d9393a8b
Content 330d6662dcbc132ecf312ac4327a5849f8d1776bafa617aed57c167e9cda47aa

Second result: full recordtoken cost · -0.1875 tokens per declared item

Second result · 2026-08-28 16:06 UTC

different-from(ref, by=key) / different-across(group, by=key) — what is a ‘different’ choice different from?

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: -0.1875 tokens per declared item
Reported interval: -2.375 to -0.1875.
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, tiktoken/o200k_base, tiktoken/p50k_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: 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 -0.1875 tokens; the current declaration allows at most 2 tokens.

Has the original estimate been independently reproduced?

Agrees with the named original. This replication reports -0.1875 tokens; the named original reported -0.1875.

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.

How can one check pass while the other does not?

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 identity

330d6662dcbc132ecf312ac4327a5849f8d1776bafa617aed57c167e9cda47aa

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

English input: Choice 01: select a dataset whose license-id is unequal to the reference dataset's license-id.
Ainglish input: Choice 01: select a dataset different-from(reference-dataset, by=license-id).

Input 2

English input: Choice 01: assign a dataset to every reviewer such that distinct reviewers' selected license-id values are pairwise unequal.
Ainglish input: Choice 01: assign a dataset to every reviewer different-across(reviewers, by=license-id).

Input 3

English input: Choice 02: select a image whose digest is unequal to the reference image's digest.
Ainglish input: Choice 02: select a image different-from(reference-image, by=digest).

Input 4

English input: Choice 02: assign a image to every reviewer such that distinct reviewers' selected digest values are pairwise unequal.
Ainglish input: Choice 02: assign a image to every reviewer different-across(reviewers, by=digest).

Input 5

English input: Choice 03: select a wallet whose owner-id is unequal to the reference wallet's owner-id.
Ainglish input: Choice 03: select a wallet different-from(reference-wallet, by=owner-id).

Input 6

English input: Choice 03: assign a wallet to every reviewer such that distinct reviewers' selected owner-id values are pairwise unequal.
Ainglish input: Choice 03: assign a wallet to every reviewer different-across(reviewers, by=owner-id).

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

Not recorded

Reader or tokenizer results

[
    {
        "model": "tiktoken\/cl100k_base",
        "value": -1.84375
    },
    {
        "model": "tiktoken\/o200k_base",
        "value": -2.375
    },
    {
        "model": "tiktoken\/p50k_base",
        "value": -0.1875
    }
]

Condition results

Not recorded

Exact result and immutable specification Experiment history

Attempt 88447004-b1e6-4b6b-b141-d088e6c5901d
Content 07a17e7cb665ff96be06dbd459422ad7d17d2d36ad51a6fee4f5e96f4fac4ca8

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.