Instrument invalid. This is inactive history. Its reported value is preserved, but it cannot currently support or oppose inclusion.
What was measured
token cost · token_delta How does the wording change tokenizer units for the declared tokenizer population?
Historical reported result
-15.5 tokens per declared item Reported interval: -15.5625 to -15.5.
This is inactive history. Its reported value is preserved, but it cannot currently support or oppose inclusion.
English comparison
Complete, careful English
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
Reader population not separately declared.
Conditions covered
Separate outcomes retained for all 2 declared conditions
part-capped, part-chosen
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 is inactive history. Its reported value is preserved, but it cannot currently support or oppose inclusion.
Is this result within the cost allowance?
This headline is within the allowance.
The reported difference is -15.5 tokens; the current declaration allows at most 8 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?
Inactive history.
This is inactive history. Its reported value is preserved, but it cannot currently support or oppose inclusion.
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. This historical row does not count.
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.
Condition
Reported difference
Reported interval
part-capped
-15.25
Not recorded
part-chosen
-15.75
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
I examined the 48 alerts that the severity-quartile rule chose, out of the 193 recorded; the rule picked which alerts to examine.
Ainglish input
part-chosen(severity-quartile): the 48 alerts.
Condition
part-chosen
Input 2
English input
I reviewed the 72 suppliers that the alphabetic-slice rule chose, out of the 418 listed; the rule picked which suppliers to review.
Ainglish input
part-chosen(alphabetic-slice): the 72 suppliers.
Condition
part-chosen
Input 3
English input
I inspected the 96 sessions that random seed 77 chose, out of the 630 captured; that rule picked which sessions to inspect.
Ainglish input
part-chosen(random-seed-77): the 96 sessions.
Condition
part-chosen
Input 4
English input
I checked the 35 clinics that the region rule chose, out of the 204 registered; the rule picked which clinics to check.
Ainglish input
part-chosen(region-rule): the 35 clinics.
Condition
part-chosen
Input 5
English input
I audited the 60 certificates that the age-window rule chose, out of the 355 issued; the rule picked which certificates to audit.
Ainglish input
part-chosen(age-window): the 60 certificates.
Condition
part-chosen
Input 6
English input
I traced the 44 deliveries that the weekday rule chose, out of the 287 logged; the rule picked which deliveries to trace.
Ainglish input
part-chosen(weekday-rule): the 44 deliveries.
Condition
part-chosen
Recorded input digest: fe2831507843811435c7a3511d420c9e83d0981eacdf1ee197ef62cb5de333a0
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
Ainglish form versus complete careful English
Tested population
16 frozen fresh pairs across part-capped and part-chosen
Unit tested
complete message
How results combine
equal item mean per stratum, weighted by stratum share, 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.
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.