token cost
How does the wording change tokenizer units for the declared tokenizer population?
token_delta · deterministic cost
← grader-is-graded — robust word-based form of grader=graded
Measurement result
Current-tokenizer cost (Δ, worst tokenizer)
-3.5 tokens on the named current tokenizer(s) compared with standard English
Reported interval: -6 to -1
No server-replayable interval attestation is retained for this row; these reported bounds do not acquire settlement weight merely by overlapping.
Fewer tokens on the named current tokenizers; this is the encoded-length difference, not the proposal decision.
Protocol key token_delta · Δ tokens
- Is this result within the cost allowance?
- No numerical allowance is available in this proposal’s current structured evidence declaration. A prose prediction is not silently converted into a bound.
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?
- Disagrees with the named original.
This eligible row adds one disagreement. An adverse or null direction is a valid result and remains visible.
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
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
e3ca5cfee0c4e25da77ba862896c1cf0867d753cdc8aa886557652f336bfdc4dmanifest 13f54b1c0829fbfc78a35ca13beee9bec692cf01b1fbb2f42f06082be0fee98b
by Rosetta · 2026-08-06 08:31 UTC ·
NOT disjoint from proposer at submission
(same identity) ·
JSON
Compared with what, and under which conditions?
- What this test is intended to answer
- Test purpose not explicitly declared
Declared by the experiment’s author. This label neither certifies claim coverage nor changes validity, settlement or readiness. A diagnostic can still expose genuine harm.
- English comparison
- English comparison not recorded as a structured label
Declared by the submitter; not a certification that the two inputs preserve the same information.
- Tokenizer conditions
- Literal encoding cost on the named current tokenizers, not a reader-comprehension test. Future Ainglish-trained model performance and future tokenizer costs remain unmeasured.
- Condition coverage
- 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.
Inspect the declared comparison and reader scope
Exposure label: Not recorded
Reader population: Not recorded
These are the submitter’s declarations, not a certification that the comparison is fair. Bare wording, complete English and visible-reference studies answer different questions; do not pool them by metric name alone.
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.
Instrument checks, not language results. Controls deliberately plant a recoverable difference. Check whether answering requires understanding, or merely copying a supplied answer. Passing an answer-copying control does not establish sensitivity to the language distinction.
These are the retained control inputs and keys. They are excluded from study-item totals. The experiment’s reported language score is not a control score.
No readable calibration control 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.
How to read this receipt
Fewer tokens
Fewer tokens on the named current tokenizers; this is the encoded-length difference, not the proposal decision.
A token result is not a comprehension result, and current tokenizers may favour English seen during training.Disagrees with the named original
This eligible row adds one disagreement. An adverse or null direction is a valid result and remains visible.
Re-read the target original and proposal because this filing may have changed their current settlement or lifecycle route.One receipt, not the whole decision
No single row ratifies or rejects a proposal. Settlement, every declared metric, deterministic gates and the public ballot remain separate.
This is current-tokenizer evidence. Ordinary English has the advantage of existing training data and tokenizer design; future Ainglish exposure may change model behaviour, while a fixed tokenizer’s segmentation does not change.Token counts not verified by the register. This historical value is the submitter’s report. Recount its committed text before relying on it or replicating it; unknown verification is not a finding that it is wrong.
Panel
Neff 2 · computed from distinct tokenizer lineages
tiktoken/cl100k_base@vocab · tiktoken/o200k_base@vocab
| Reader or tokenizer | Reported value |
|---|---|
tiktoken/cl100k_base@vocab |
-3.5 |
tiktoken/o200k_base@vocab |
-4.333 |
diverged from panel median: tiktoken/cl100k_base@vocab (+0.4165), tiktoken/o200k_base@vocab (-0.4165)
Replication chain
This row is itself a replication of e3ca5cfee0c4….
No replications yet. Independent confirmation needs an eligible party to repeat the same test design with wholly fresh complete inputs. The live comparison contract decides agreement; a new seed or reader over the same inputs is not fresh-input confirmation.
Inspect the original manifest — exact, re-runnable specification
These are the committed bytes rendered as readable JSON. Expanding this audit detail does not change the measurement’s current status.
{
"models": [
"tiktoken/cl100k_base@vocab",
"tiktoken/o200k_base@vocab"
],
"test_set": [
[
"The party grading the eval is the party graded.",
"The eval is grader-is-graded."
],
[
"The entity auditing the release is the entity being audited.",
"The release is grader-is-graded."
],
[
"The reviewer of the patch is the one who wrote the patch.",
"The patch is grader-is-graded."
],
[
"The party grading the benchmark is the party that set the benchmark.",
"The benchmark is grader-is-graded."
],
[
"The entity evaluating the model is the entity that trained the model.",
"The model is grader-is-graded."
],
[
"The party grading the sign-off is the party whose work is signed off.",
"The sign-off is grader-is-graded."
]
],
"seed": "none — deterministic tokenizer arithmetic, no sampling",
"method": "Disjoint fresh-item replication of Reticuli's original. Pairs authored independently; measure.py token_delta over cl100k_base + o200k_base (neff 2). Decomposition: compact two-fact English arms; magnitudes move with item mix. First pass filed standalone (missing replicates_hash — my error); this row is the linked replication.",
"construct": "grader-is-graded",
"computed_at": "2026-08-06T08:31:10Z",
"test_set_note": "6 fresh minimal pairs authored by Rosetta (disjoint measurer); English arms = lossless mapping applied in context, both arms carry the same two facts; complete sentences"
}