Each criterion is scored on a 0–10 scale (0 = poor, 10 = outstanding). We are open to adjusting the criteria based on community feedback.
| # | Criterion | Description | Score Range | Interpretation |
|---|---|---|---|---|
| 1 | Mathematical Rigour | Depth and correctness of derivations, proofs, and definitions; precision and consistency. | 0–10 | Superficial → fully rigorous and formal. |
| 2 | Conceptual Clarity | Clarity of abstract ideas (e.g., vector spaces, Linear maps) without distortion or oversimplification. | 0–10 | Confusing → clear, intuitive, and precise. |
| 3 | Pedagogical Design | Logical flow, scaffolding, exercises, and self‑study suitability. | 0–10 | Disjointed → well structured and supportive. |
| 4 | Relevance to ML/QC Applications | Accurate links to ML and quantum algorithms, coding examples, or physical analogues. | 0–10 | Purely abstract → deeply connected to practice. |
| 5 | Notation Consistency & Accessibility | Standard, consistent notation; clear glossary; minimal overload or ambiguity. | 0–10 | Idiosyncratic → clean and widely interpretable. |
| 6 | Originality of Approach | Novel presentation, unifying perspectives, or new pedagogical insights. | 0–10 | Derivative → fresh, insightful approach. |
| 7 | Breadth vs Depth Balance | Coverage breadth without superficiality; depth where it matters. | 0–10 | Unbalanced → comprehensive and proportional. |
| 8 | Practical Utility | Worked examples, exercises, code, and reproducible resources. | 0–10 | Impractical → excellent theory–practice bridge. |
| 9 | Historical & Theoretical Context | Lineage of ideas, citations to primary sources, conceptual framing and motivation. | 0–10 | Absent → rich, well contextualized narrative. |
| 10 | Overall Coherence & Quality | Internal consistency, polish, and contribution to the literature. | 0–10 | Disjointed → cohesive, enduring quality. |
Total possible score: 0–100