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# Example: conflicting reviewers
This synthetic example shows how editor instructions and evidence limits control the response when
reviewers request incompatible claim strength.
## Input
```text
Editor:
Please avoid expanding the manuscript substantially and focus on clarifying the central claim.
Reviewer 1:
1. The abstract should make a stronger causal claim that X drives Y.
Reviewer 2:
1. The causal language is not supported by the observational design and should be softened.
Author notes:
- The study is observational.
- We can soften the abstract and discussion.
- We can state that the findings support an association, not causality.
```
## Expected handling
- Assign the editor instruction `E.1`.
- Assign reviewer comments `R1.1` and `R2.1`.
- Surface the conflict in the strategy summary.
- Prioritize the editor instruction and the observational design.
- Use `SOFTEN_CLAIM` for `R2.1`.
- Use `PARTIAL` or `DISAGREE` for `R1.1`, with respectful reasoning.
## Response style
```text
We appreciate the reviewer's suggestion to sharpen the abstract. However, because the study is
observational, we agree with the editor's instruction to clarify the central claim without
overstating causality. We have therefore revised the abstract and Discussion to state that the
findings support an association between X and Y, rather than a causal relationship.
```
The response must not promise both stronger causal language and softened causal language.

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# Example: major revision with missing evidence
This synthetic example shows how to avoid fabricated compliance when an author note is incomplete.
## Input
```text
Editor decision: Major revision.
Reviewer 1:
1. The manuscript requires validation in an independent cohort.
2. The replicate definition in the statistical analysis is unclear.
Author notes:
- We added validation using dataset GSEXXXX in Fig. 5.
- We fixed the statistics description.
```
## Expected handling
```text
Response strategy summary
- Decision type: Major revision
- Task mode: draft
- Package readiness: needs_author_input
- Major risks: validation results and statistical details are missing
```
The response may mention `GSEXXXX` and `Fig. 5` because they were supplied. It must not invent:
- validation performance;
- sample size;
- p-values;
- confidence intervals;
- statistical test names;
- Methods or Results line numbers.
## Required author questions
```text
Missing information / risk flags
- R1.1: Please provide the validation result summary, cohort size or dataset scale, and Results/Fig. 5 location.
- R1.2: Please provide the statistical test name, replicate unit, sample size, correction method, and Methods location.
```
## Response style
```text
To address this concern, we added an independent validation analysis using dataset GSEXXXX,
which is presented in Fig. 5. The final response requires the validation result summary and
manuscript location before it can be marked ready_to_submit.
```

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# Example: minor revision response package
This synthetic example shows the expected output shape for a minor revision. It is not based on
real reviewer comments.
## Input
```text
Editor decision: Minor revision.
Reviewer 1:
1. Please define cross-domain calibration in the Introduction.
2. Figure 2 legend does not explain the colour scale.
Author notes:
- Cross-domain calibration means adjusting the model output across datasets with different feature distributions.
- We added a definition in the Introduction.
- We revised the Figure 2 legend to define the colour scale.
- No line numbers are available.
```
## Expected response strategy summary
```text
Response strategy summary
- Decision type: Minor revision
- Task mode: draft
- Package readiness: draft_with_placeholders
- Overall posture: Cooperative and concise
- Major risks: line numbers are not available
- Suggested ordering: Reviewer 1 comments in order
```
## Expected tracker
```markdown
| ID | Reviewer concern | Type | Severity | Proposed action | Readiness | Missing author input |
|---|---|---|---|---|---|---|
| R1.1 | Define cross-domain calibration | Editorial / presentation | Minor | ACCEPT_TEXT | draft_with_placeholders | Line or section location |
| R1.2 | Explain Figure 2 colour scale | Editorial / figure | Minor | ACCEPT_FIGURE | draft_with_placeholders | Line or legend location |
```
## Response style
```text
We agree that the original Introduction did not define this term clearly. We have revised the
Introduction to define cross-domain calibration as adjustment of model output across datasets with
different feature distributions. This change appears in the Introduction [location].
```
Do not invent line numbers.