Find Precedents

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

Select Source Case
Source Case: Use of Artificial Intelligence in Engineering Practice

Case Number: 24-02

Year: 2025

Found 10 Precedents

Ranked by weighted similarity score
Matching Methods:
Cosine Semantic embedding similarity Jaccard Set intersection / union Categorical Exact match scoring
Similarity Components
Facts Similarity Cosine
46%
Discussion Similarity Cosine
52%
Provision Overlap Jaccard
23%
Outcome Match Categorical
100%
Subject Tags Jaccard
36%
Principle Tensions Jaccard
0%
What They Share

Provisions: I.1 II.2.b III.8.a

Topics: Competence Licensure Laws Signing Plans/Documents +1

Outcome: Both Unethical

Pattern: Stalemate vs Transfer

Similarity Components
Facts Similarity Cosine
49%
Discussion Similarity Cosine
45%
Provision Overlap Jaccard
15%
Outcome Match Categorical
100%
Subject Tags Jaccard
33%
Principle Tensions Jaccard
0%
What They Share

Provisions: III.8.a III.9

Topics: Licensure Laws Advertising Credit for Engineering Work +1

Outcome: Both Unethical

Pattern: Both Stalemate

Similarity Components
Facts Similarity Cosine
50%
Discussion Similarity Cosine
47%
Provision Overlap Jaccard
15%
Outcome Match Categorical
100%
Subject Tags Jaccard
25%
Principle Tensions Jaccard
0%
What They Share

Provisions: I.1 III.8.a

Topics: Licensure Laws Advertising Duty to the Public

Outcome: Both Unethical

Pattern: Both Stalemate

Similarity Components
Facts Similarity Cosine
45%
Discussion Similarity Cosine
51%
Provision Overlap Jaccard
8%
Outcome Match Categorical
100%
Subject Tags Jaccard
18%
Principle Tensions Jaccard
0%
What They Share

Provisions: I.2

Topics: Competence Qualifications for Work

Outcome: Both Unethical

Pattern: Both Stalemate

Similarity Components
Facts Similarity Cosine
42%
Discussion Similarity Cosine
52%
Provision Overlap Jaccard
8%
Outcome Match Categorical
100%
Subject Tags Jaccard
17%
Principle Tensions Jaccard
0%
What They Share

Provisions: I.1

Topics: Advertising Duty to the Public

Outcome: Both Unethical

Pattern: Both Stalemate

Similarity Components
Facts Similarity Cosine
50%
Discussion Similarity Cosine
41%
Provision Overlap Jaccard
7%
Outcome Match Categorical
100%
Subject Tags Jaccard
12%
Principle Tensions Jaccard
0%
What They Share

Provisions: I.1

Topics: Advertising Duty to the Public

Outcome: Both Unethical

Pattern: Stalemate vs Transfer

Similarity Components
Facts Similarity Cosine
37%
Discussion Similarity Cosine
45%
Provision Overlap Jaccard
0%
Outcome Match Categorical
100%
Subject Tags Jaccard
0%
Principle Tensions Jaccard
0%
What They Share

Outcome: Both Unethical

Pattern: Both Stalemate

Similarity Components
Facts Similarity Cosine
29%
Discussion Similarity Cosine
38%
Provision Overlap Jaccard
10%
Outcome Match Categorical
100%
Subject Tags Jaccard
0%
Principle Tensions Jaccard
0%
What They Share

Provisions: I.1

Topics: Advertising Duty to the Public

Outcome: Both Unethical

Pattern: Both Stalemate

Similarity Components
Facts Similarity Cosine
40%
Discussion Similarity Cosine
48%
Provision Overlap Jaccard
7%
Outcome Match Categorical
50%
Subject Tags Jaccard
6%
Principle Tensions Jaccard
0%
What They Share

Provisions: I.1

Topics: Duty to the Public

Outcome: None vs Unclear

Pattern: Both Stalemate

Similarity Components
Facts Similarity Cosine
38%
Discussion Similarity Cosine
49%
Provision Overlap Jaccard
6%
Outcome Match Categorical
50%
Subject Tags Jaccard
6%
Principle Tensions Jaccard
0%
What They Share

Provisions: I.1

Topics: Duty to the Public

Outcome: None vs Mixed

Pattern: Stalemate vs Transfer

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