Find Precedents

Multi-factor similarity search using provision overlap, semantic similarity, and outcome alignment.

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Source Case: Independence of Peer Reviewer

Case Number: 22-8

Year: 2022

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Found 10 Precedents

Ranked by weighted similarity score
Matching Methods:
Cosine Semantic embedding similarity Jaccard Set intersection / union Categorical Exact match scoring
44% Similar
Similarity Components
Facts Similarity Cosine
28%
Discussion Similarity Cosine
48%
Provision Overlap Jaccard
36%
Outcome Match Categorical
100%
Subject Tags Jaccard
36%
Principle Tensions Jaccard
0%
What They Share

Provisions: I.1 I.4 I.6 +1

Topics: Employer Faithful Agents and Trustees Errors +1

Outcome: Both Unclear

Pattern: Both Stalemate

39% Similar
Similarity Components
Facts Similarity Cosine
30%
Discussion Similarity Cosine
53%
Provision Overlap Jaccard
40%
Outcome Match Categorical
50%
Subject Tags Jaccard
38%
Principle Tensions Jaccard
0%
What They Share

Provisions: I.4 I.6 II.1.c +1

Topics: Employer Faithful Agents and Trustees Confidential Information

Outcome: None vs Mixed

Pattern: Stalemate vs Transfer

34% Similar
Similarity Components
Facts Similarity Cosine
26%
Discussion Similarity Cosine
49%
Provision Overlap Jaccard
0%
Outcome Match Categorical
100%
Subject Tags Jaccard
25%
Principle Tensions Jaccard
0%
What They Share

Topics: Faithful Agents and Trustees Duty to the Public

Outcome: Both Unclear

Pattern: Stalemate vs Transfer

32% Similar
Similarity Components
Facts Similarity Cosine
38%
Discussion Similarity Cosine
40%
Provision Overlap Jaccard
23%
Outcome Match Categorical
50%
Subject Tags Jaccard
25%
Principle Tensions Jaccard
0%
What They Share

Provisions: I.1 I.4 III.1.a

Topics: Employer Faithful Agents and Trustees Errors +1

Outcome: None vs Ethical

Pattern: Stalemate vs Transfer

32% Similar
Similarity Components
Facts Similarity Cosine
31%
Discussion Similarity Cosine
44%
Provision Overlap Jaccard
21%
Outcome Match Categorical
50%
Subject Tags Jaccard
30%
Principle Tensions Jaccard
0%
What They Share

Provisions: I.4 I.6 III.4

Topics: Employer Faithful Agents and Trustees Confidential Information

Outcome: None vs Ethical

Pattern: Both Stalemate

29% Similar
Similarity Components
Facts Similarity Cosine
40%
Discussion Similarity Cosine
48%
Provision Overlap Jaccard
10%
Outcome Match Categorical
50%
Subject Tags Jaccard
10%
Principle Tensions Jaccard
0%
What They Share

Provisions: III.7.a

Topics: Reviewing the Work of Other Engineers

Outcome: None vs Unethical

Pattern: Both Stalemate

29% Similar
Similarity Components
Facts Similarity Cosine
30%
Discussion Similarity Cosine
42%
Provision Overlap Jaccard
15%
Outcome Match Categorical
50%
Subject Tags Jaccard
23%
Principle Tensions Jaccard
0%
What They Share

Provisions: I.1 I.4

Topics: Employer Faithful Agents and Trustees Duty to the Public

Outcome: None vs Unethical

Pattern: Stalemate vs Transfer

28% Similar
Similarity Components
Facts Similarity Cosine
0%
Discussion Similarity Cosine
0%
Provision Overlap Jaccard
33%
Outcome Match Categorical
100%
Subject Tags Jaccard
50%
Principle Tensions Jaccard
0%
What They Share

Provisions: I.1 I.4 II.1.c +1

Topics: Employer Faithful Agents and Trustees Confidential Information +1

Outcome: Both Unclear

Pattern: Stalemate vs Transfer

27% Similar
Similarity Components
Facts Similarity Cosine
30%
Discussion Similarity Cosine
50%
Provision Overlap Jaccard
11%
Outcome Match Categorical
50%
Subject Tags Jaccard
0%
Principle Tensions Jaccard
0%
What They Share

Provisions: I.1

Topics: Duty to the Public

Outcome: None vs Unethical

Pattern: Both Stalemate

27% Similar
Similarity Components
Facts Similarity Cosine
41%
Discussion Similarity Cosine
42%
Provision Overlap Jaccard
8%
Outcome Match Categorical
50%
Subject Tags Jaccard
9%
Principle Tensions Jaccard
0%
What They Share

Provisions: I.1

Topics: Duty to the Public

Outcome: None vs Unethical

Pattern: Both Stalemate

References View all

Richter, M.M. & Weber, R.O. (2013). Case-Based Reasoning: A Textbook. Springer. ISBN: 978-3-642-40166-4.

Reimers, N. & Gurevych, I. (2019). Sentence-BERT: Sentence embeddings using Siamese BERT-Networks. Proceedings of EMNLP-IJCNLP 2019, pp. 3982-3992. DOI: 10.18653/v1/D19-1410

Sun, Z., Zhang, K., Yu, W., Wang, H. & Xu, J. (2024). Logic rules as explanations for legal case retrieval. Proceedings of LREC-COLING 2024, pp. 10747-10759. ACL Anthology

Wiratunga, N., et al. (2024). CBR-RAG: Case-based reasoning for retrieval augmented generation in LLMs for legal question answering. arXiv preprint arXiv:2404.04302. arXiv

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