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@@ -1,129 +1,60 @@
 ---
-dataset_info:
-  features:
-  - name: narrative
-    dtype: string
-  - name: question
-    dtype: string
-  - name: choices
-    dtype: string
-  - name: answer_index
-    dtype: int64
-  - name: answer_choice
-    dtype: string
-  - name: task_source
-    dtype: string
-  - name: formatted_prompt
-    list:
-    - name: content
-      dtype: string
-    - name: role
-      dtype: string
-  - name: response
-    list: string
-  - name: formatted_prompt__metadata
-    list:
-    - name: endpoint_type
-      dtype: string
-    - name: litellm_function
-      dtype: string
-    - name: model
-      dtype: string
-    - name: raw_prompt
-      list:
-      - name: content
-        dtype: string
-      - name: role
-        dtype: string
-    - name: raw_system_prompt
-      dtype: 'null'
-    - name: request_payload
-      dtype: string
-  - name: response__metadata
-    list:
-    - name: cost
-      dtype: float64
-    - name: finish_reason
-      dtype: string
-    - name: input_tokens
-      dtype: int64
-    - name: model
-      dtype: string
-    - name: output_tokens
-      dtype: int64
-    - name: raw_response
-      dtype: string
-  - name: eval_result
-    list: bool
-  - name: eval_result__metadata
-    list:
-    - name: correct_answer_index
-      dtype: int64
-    - name: correct_answer_number
-      dtype: int64
-    - name: correct_answer_text
-      dtype: string
-    - name: extracted_number
-      dtype: int64
-    - name: extracted_text
-      dtype: string
-    - name: extractor
-      dtype: string
-    - name: matched_by
-      dtype: string
-    - name: num_choices
-      dtype: int64
-    - name: raw_line
-      dtype: string
-  - name: _judge_prompt__metadata
-    list:
-    - name: endpoint_type
-      dtype: string
-    - name: litellm_function
-      dtype: string
-    - name: model
-      dtype: string
-    - name: raw_prompt
-      list:
-      - name: content
-        dtype: string
-      - name: role
-        dtype: string
-    - name: raw_system_prompt
-      dtype: 'null'
-    - name: request_payload
-      dtype: string
-  - name: _judge_response__metadata
-    list:
-    - name: cost
-      dtype: float64
-    - name: finish_reason
-      dtype: string
-    - name: input_tokens
-      dtype: int64
-    - name: model
-      dtype: string
-    - name: output_tokens
-      dtype: int64
-    - name: raw_response
-      dtype: string
-  - name: strategy_compliance
-    dtype: int64
-  - name: compliance_reasoning
-    dtype: string
-  - name: compliance_elements_followed
-    list: string
-  - name: compliance_elements_missed
-    list: string
-  splits:
-  - name: train
-    num_bytes: 629008
-    num_examples: 10
-  download_size: 323307
-  dataset_size: 629008
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+license: mit
+tags:
+- strategy_compliance
+- musr
+- murder_mysteries
+- reasoning_malleability
+- baseline
 ---
+
+# t1-strategy-musr-baseline-qwen3-80b-instruct-musr-base
+
+**Strategy compliance** evaluation on MuSR murder mysteries — **baseline** variant.
+
+Model received standard MuSR cot+ prompt (baseline control). Judge still scores against criterion-first rubric.
+Compliance is scored by an LLM judge (1-5 Likert) against the Criterion-First rubric.
+
+## Results
+
+| Metric | Value |
+|--------|-------|
+| pass@1 | 0.8000 |
+| Strategy compliance (mean) | 2.90 |
+| Strategy compliance (min) | 2 |
+| Strategy compliance (max) | 4 |
+| Total problems | 10 |
+
+### Compliance Distribution
+
+| Score | Count | Meaning |
+|-------|-------|---------|
+| 1 | 0 | Non-compliant |
+| 2 | 5 | Minimal |
+| 3 | 1 | Partial |
+| 4 | 4 | Mostly compliant |
+| 5 | 0 | Fully compliant |
+
+## Details
+
+| Parameter | Value |
+|-----------|-------|
+| Model | `together_ai/Qwen/Qwen3-Next-80B-A3B-Instruct` |
+| Thinking | False |
+| Temperature | 0.7 |
+| Max tokens | 32768 |
+| Judge model | `openai/gpt-4o-mini` |
+| Num examples | 10 |
+| Variant | baseline |
+
+## Usage
+
+```python
+from datasets import load_dataset
+ds = load_dataset("reasoning-degeneration-dev/t1-strategy-musr-baseline-qwen3-80b-instruct-musr-base", split="train")
+scores = ds["strategy_compliance"]
+print(f"Mean compliance: {sum(scores) / len(scores):.2f}")
+```
+
+---
+*Tracked in [reasoning-degeneration-dev/PROJECT-MANIFEST](https://huggingface.co/datasets/reasoning-degeneration-dev/PROJECT-MANIFEST)*