Not yet counting in evidence decisions. This row remains available for assessment, but does not currently carry a counting evidence result.
What was measured
comprehension accuracy · comprehension_accuracy_delta How does the wording change correct answers from the declared reader panel?
Reported result
-16.67 percentage points Reported interval: -50 to 0.
The value is neutral or does not resolve the registered direction.
English comparison
Complete, careful English
Declared by the submitter; not a certification of equivalent information.
Complete careful-English expansion.
Reader exposure
Reader exposure not recorded as a structured label
Named instruments
spark-zen-13-minimal
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.
How often did each version lead to the right answer?
English comparison
100.00%
100.00%
Ainglish version
83.33%
83.33%
Reported real-item accuracy, not the separate calibration score. Both bars use the same 0–100% scale. The difference is measured in percentage points, not percent improvement. Any declared stratum weights are already applied.
Reported item-bootstrap interval: -50 to 0 percentage points.
This interval concerns the difference, not separate uncertainty bounds for either accuracy. It does not measure uncertainty across humans or future models.
Real cases: 12 · Named readers: 1. These are different units; multiple answers to one case are not new cases.
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 12 readable, inline study items, in stored order—not a selection of successes. 4 control items are kept separate.
Each result has its own input pages. Positions across the two studies do not imply matched cases.
Input 5 · real-o1
English input
My grep tool reports no TODOs remain; I did not witness the tree myself.
Ainglish input
obs(grep): no TODOs remain.
Question
Did the speaker witness the tree?
Recorded answer options
yes · no
Submitted answer key
no. This is the supplied key, not an independent validation of it.
Filed correctness against that key (up to 12 reader/arm cells). These flags are not the reader’s verbatim output.
spark-zen-13-minimal · English: matched the submitted key.
Input 6 · real-o2
English input
I directly observed that the vault door stands open.
Ainglish input
obs: the vault door stands open.
Question
Did the speaker directly observe it?
Recorded answer options
yes · no
Submitted answer key
yes. This is the supplied key, not an independent validation of it.
Filed correctness against that key (up to 12 reader/arm cells). These flags are not the reader’s verbatim output.
spark-zen-13-minimal · Ainglish: matched the submitted key.
Input 7 · real-o3
English input
My checksum tool reports a match; the bytes were not witnessed by me.
Ainglish input
obs(checksum): the snapshot matches.
Question
Is the match a witnessed fact?
Recorded answer options
no · yes
Submitted answer key
no. This is the supplied key, not an independent validation of it.
Filed correctness against that key (up to 12 reader/arm cells). These flags are not the reader’s verbatim output.
spark-zen-13-minimal · Ainglish: did not match the submitted key.
Input 8 · real-i1
English input
I infer the fault is external from latency data and the vendor note; the conclusion is only as strong as the weaker premise.
Ainglish input
inf(latency, vendor-note): the fault is external.
Question
May the conclusion outrun its weaker premise?
Recorded answer options
no · yes
Submitted answer key
no. This is the supplied key, not an independent validation of it.
Filed correctness against that key (up to 12 reader/arm cells). These flags are not the reader’s verbatim output.
spark-zen-13-minimal · English: matched the submitted key.
Input 9 · real-i2
English input
I infer from queue depth that the drain will finish by dawn; this is inference, not observation.
Ainglish input
inf(queue-depth): the drain will finish by dawn.
Question
Was the finish observed?
Recorded answer options
yes · no
Submitted answer key
no. This is the supplied key, not an independent validation of it.
Filed correctness against that key (up to 12 reader/arm cells). These flags are not the reader’s verbatim output.
spark-zen-13-minimal · Ainglish: matched the submitted key.
Input 10 · real-i3
English input
I infer from two green runs that the flake is gone; restating it does not strengthen it.
Ainglish input
inf(two-green-runs): the flake is gone.
Question
Does restating the inference upgrade it?
Recorded answer options
yes · no
Submitted answer key
no. This is the supplied key, not an independent validation of it.
Filed correctness against that key (up to 12 reader/arm cells). These flags are not the reader’s verbatim output.
spark-zen-13-minimal · English: matched the submitted key.
Recorded input digest: 07143861b129e7d80720a0c5c7a4e0669b40626f417f885321810a8645c08d9b
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.
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.
