EXPERIMENT NOTEBOOK · #001

How well do AI systems produce technical revision notes?

An exploratory qualitative review of three outputs created from a technical report about generative AI in automated curricular synthesis.

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Preliminary findings — interpret cautiously. The scores below are evaluator-assigned ratings, not statistical benchmark results. Output A appears to be a verbatim copy of the source report, and it is unclear whether this was a model response or a material-submission error. The exact shared task prompt and verified model-to-output mapping are unavailable. We therefore do not rank ChatGPT, Gemini, or Claude by name.

Research question

When given a technical source report, how well do generated revision notes preserve source meaning, cover important content, communicate clearly, organize information, and identify actionable revision issues?

Method at a glance

Provisional independent-evaluator scores

The table reproduces the second evaluator's criterion ratings. Weighted totals below are corrected using each rating divided by 5, multiplied by the criterion weight.

CriterionWeightOutput AOutput BOutput C
Accuracy and source fidelity35%5/54/55/5
Coverage25%5/55/55/5
Clarity15%4/54/55/5
Organization10%4/53/55/5
Revision usefulness15%1/53/55/5
Corrected weighted total100%83/10080/100100/100

Calculation: Σ (criterion rating ÷ 5 × criterion weight). The second evaluator initially reported 78 for B and 98 for C; both totals were corrected to 80 and 100 respectively. Correct arithmetic does not resolve uncertainty about material authenticity.

What the review suggests

Output A

The evaluator found that A reproduces the source verbatim. That makes it unsuitable as revision notes, but its origin is unresolved: it may be a model repeating the input or an accidental source-text substitution. Its score should not be treated as comparable evidence of model performance.

Output B

The evaluator described B as a broad structured summary, with some formatting problems and limited explicit criticism of the source report.

Output C

The evaluator rated C highest for readable structure and source-critical analysis, including attention to missing empirical measures, unclear configurations, wording defects, and tension between source-fidelity instructions and reported external contextualization.

Source-report concerns identified

Limitations

Scoring method

Each criterion is rated from 1 to 5. Its contribution to the total is the rating divided by 5, multiplied by the criterion weight. The five weights sum to 100%.

CriterionWeightEvaluation focus
Accuracy and source fidelity35%Faithfulness to source claims and qualifications; unsupported additions.
Coverage25%Coverage of important sections, findings, limitations, and recommendations.
Clarity15%Readability, precision, and explanation.
Organization10%Logical structure, headings, and scannability.
Revision usefulness15%Actionable edits and identification of source weaknesses.

Formula: Weighted total = Σ [(criterion rating ÷ 5) × criterion weight]. For example, a rating of 4/5 on a 35%-weighted criterion contributes 28 points. The published totals for B and C were corrected from 78 to 80 and 98 to 100 after arithmetic review.

Reproducibility record

This record distinguishes information available in the current audit from details that could not be verified from the materials reviewed. Missing details are not inferred.

ItemCurrent status
Source reportTitle and text are available in the working conversation; a downloadable public research archive has not been added.
Exact shared task promptNot recovered / not verified.
Model names and versions for A/B/COutput-to-model mapping is unverified; do not attribute the scores to named models.
Run dates and settingsExact run dates, model versions, and generation settings have not been verified.
Complete outputs A/B/CSome output files are available in the working materials; authenticated, labeled originals have not all been confirmed for a public archive.
Evaluation recordsAn initial qualitative audit and a second evaluator's written ratings are available. A second independent human scoring pass has not been completed.
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Material-authenticity caution. Output A was identified by the second evaluator as word-for-word identical to the source report. The available record cannot distinguish an AI verbatim-copy response from an accidental submission error. Its score is retained as a record of the evaluated material, but Output A is not valid evidence for ranking model performance until its origin is established.

Research archive checklist

The following items remain to be assembled before this experiment can be described as reproducible: (1) the exact shared prompt; (2) the source report as supplied; (3) each complete, original output labeled A/B/C; (4) model/version and run date for each output where recoverable; (5) the rubric and evaluator score sheets; and (6) a short change log recording the corrected weighted totals. Until then, this page is a transparent preliminary record, not a complete replication package.

Conclusion

In the second evaluator's assessment, Output C received the highest provisional rating, followed by A and B. Because A may be the source report itself and the shared prompt and model attribution remain unresolved, these scores are best treated as an exploratory record of the supplied materials—not a definitive model ranking or validated benchmark.

Next steps

  1. Recover the original shared prompt and original unedited outputs.
  2. Verify the identity of each output and document model/version and run date where available.
  3. Have an independent human evaluator score the authenticated outputs blind to model identity.
  4. Repeat the test on additional source documents before drawing broader conclusions.

Research status: exploratory qualitative comparison. Scores last arithmetically audited 23 October 2026. No claim of statistical significance or improved student retention is made.

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