Not yet counting in evidence decisions. This row remains available for assessment, but does not currently carry a counting evidence result.
What was measured
token cost · token_delta How does the wording change tokenizer units for the declared tokenizer population?
Reported result
-0.625 tokens per declared item Reported interval: -1.875 to -0.625.
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
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
Awaiting independent settlement
An original reports one result. It does not confirm itself.
Is this result within the cost allowance?
This headline is within the allowance.
The reported difference is -0.625 tokens; the current declaration allows at most 6 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?
Awaiting independent settlement.
An original reports one result. It does not confirm itself.
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 8 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
machine-v1 models one output count: P(0)=9/10 and P(10)=1/10. Under machine-v1, the probability-weighted mean is 1.
Ainglish input
machine-v1 models one output count: P(0)=9/10 and P(10)=1/10. 1 is mean-outcome(machine-v1).
Input 2
English input
machine-v1 models one output count: P(0)=9/10 and P(10)=1/10. Under machine-v1, 0 has the highest outcome probability, ties allowed.
Ainglish input
machine-v1 models one output count: P(0)=9/10 and P(10)=1/10. 0 is likeliest-outcome(machine-v1).
Input 3
English input
plurality-v1: P(0)=2/5, P(1)=7/20, P(2)=1/4. Under plurality-v1, 0 has the highest outcome probability, ties allowed, although P(nonzero)=3/5.
Ainglish input
plurality-v1: P(0)=2/5, P(1)=7/20, P(2)=1/4. 0 is likeliest-outcome(plurality-v1), although P(nonzero)=3/5.
Input 4
English input
two-point-v1: P(0)=1/2, P(10)=1/2. Under two-point-v1, the probability-weighted mean is 5.
Ainglish input
two-point-v1: P(0)=1/2, P(10)=1/2. 5 is mean-outcome(two-point-v1).
Input 5
English input
two-point-v1: P(0)=1/2, P(10)=1/2. Both 0 and 10 have the highest outcome probability; neither is a unique mode.
Ainglish input
two-point-v1: P(0)=1/2, P(10)=1/2. Both 0 and 10 are likeliest-outcome(two-point-v1); neither is a unique mode.
Input 6
English input
distribution-A: P(5)=3/10, P(15)=7/10. Under distribution-A, the probability-weighted mean is 12.
Ainglish input
distribution-A: P(5)=3/10, P(15)=7/10. 12 is mean-outcome(distribution-A).
Recorded input digest: 5b1f6bdd9f4484bcbacfec2ae6dfd0e38695a21b07e57ea4b3676d82b6d4dcb8
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
token_delta
Tested population
cl100k_base/o200k_base/p50k_base
Unit tested
pair
How results combine
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.
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.
