Live tracker

SlopJudges

Tracking AI slop in real U.S. Supreme Court, Courts of Appeals, and federal District Court opinions. Every opinion is pulled from the public CourtListener record and scored by our own blend of an LLM judge and deterministic heuristics — no third-party detector.

Opinions analyzed
1,188
Slop opinions
33
Courts tracked
26
Last updated
Jul 28, 2026, 8:01 AM

Cumulative AI-slop opinions over time

Supreme Court vs. the regional Courts of Appeals vs. the specialized D.C. & Federal Circuits vs. the federal District Courts.

010203020192020202120222023202420252026

Justices by AI-slop opinions

Supreme Court justices ranked by opinions flagged as slop; ties break on average AI score.

  1. 1
    Barrett
    11 avg AI · 8 opinions
    AI 20
    1
    Watson v. Republican National Committee
  2. 2
    Kavanaugh
    9 avg AI · 24 opinions
    AI 18
    1
    West Virginia v. B. P. J. (Kavanaugh, Majority)
  3. 3
    Jackson
    9 avg AI · 32 opinions
    AI 17
    0
    Trump v. Cook (Jackson, concurring)
  4. 4
    Kagan
    9 avg AI · 18 opinions
    AI 16
    0
    Mullin v. Doe (Kagan, dissenting)
  5. 5
    Roberts
    8 avg AI · 9 opinions
    AI 15
    0
    Trump v. Barbara (Roberts, Majority)
  6. 7
    Gorsuch
    7 avg AI · 34 opinions
    AI 14
    0
    Trump v. Barbara (Gorsuch, dissenting)
  7. 8
    Thomas
    7 avg AI · 33 opinions
    AI 14
    0
    Bondi v. Vanderstok (Thomas, dissenting)
  8. 9
    Alito
    7 avg AI · 23 opinions
    AI 10
    0
    Chatrie v. United States (Alito, dissenting)
  9. 10
    Sotomayor
    6 avg AI · 17 opinions
    AI 10
    0
    Bondi v. Vanderstok (Sotomayor, concurring)
  10. 11
    Breyer
    6 avg AI · 6 opinions
    AI 7
    0
    Johnson v. Guzman Chavez (Breyer, dissenting)
  11. 12
    Per Curiam
    4 avg AI · 10 opinions
    AI 12
    0
    NVIDIA v. E. Ohman J:or Fonder AB
  12. 13
    Ketanji Brown Jackson
    3 avg AI · 2 opinions
    AI 4
    0
    United States v. Miller
  13. 14
    John G. Roberts
    2 avg AI · 3 opinions
    AI 3
    0
    Loper Bright Enterprises v. Raimondo
  14. 15
    Sonia Sotomayor
    2 avg AI · 2 opinions
    AI 2
    0
    Wilkinson v. Garland
  15. 16
    Amy Coney Barrett
    1 avg AI · 1 opinion
    AI 1
    0
    Acheson Hotels, LLC v. Laufer
  16. 17
    Neil Gorsuch
    1 avg AI · 4 opinions
    AI 1
    0
    Bondi v. Vanderstok
  17. 18
    Clarence Thomas
    0 avg AI · 1 opinion
    AI 0
    0
    New York State Rifle & Pistol Assn., Inc. v. Bruen

Courts by AI-slop opinions

All tracked courts ranked by opinions flagged as slop; ties break on average AI score.

  1. 1
    7th Cir.
    5 avg AI · 132 opinions
    AI 22
    9
    American Academy of Pediatrics v. James Uthmeier
  2. 2
    8th Cir.
    8 avg AI · 60 opinions
    AI 26
    7
    United States v. Calvin Carter
  3. 3
    4th Cir.
    7 avg AI · 98 opinions
    AI 50
    4
    United Financial Casualty Co. v. Greg Ball
  4. 4
    D.D.C.
    5 avg AI · 148 opinions
    AI 27
    3
    Perales v. Office of the Clerk
  5. 5
    SCOTUS
    7 avg AI · 229 opinions
    AI 20
    2
    Watson v. Republican National Committee
  6. 6
    1st Cir.
    7 avg AI · 78 opinions
    AI 23
    2
    Rana v. Blanche
  7. 7
    6th Cir.
    5 avg AI · 78 opinions
    AI 19
    2
    Eric Smith v. SEC
  8. 9
    3rd Cir.
    6 avg AI · 69 opinions
    AI 19
    1
    Savannah Byers v. Finishing Systems Inc
  9. 11
    S.D.N.Y.
    12 avg AI · 2 opinions
    AI 16
    0
    Rasberry ex rel. Situated v. Columbia Cnty.
  10. 12
    C.D. Cal.
    11 avg AI · 2 opinions
    AI 12
    0
    Vieira v. Mentor Worldwide, LLC
  11. 13
    E.D.N.Y.
    11 avg AI · 2 opinions
    AI 14
    0
    United States v. Ceasar
  12. 15
    E.D. Tex.
    7 avg AI · 2 opinions
    AI 7
    0
    True Health Diagnostics, LLC v. Azar
  13. 16
    E.D. Va.
    7 avg AI · 2 opinions
    AI 7
    0
    Elhady v. Kable
  14. 17
    N.D. Cal.
    6 avg AI · 2 opinions
    AI 7
    0
    E. Bay Sanctuary Covenant v. Barr
  15. 18
    N.D. Tex.
    6 avg AI · 2 opinions
    AI 6
    0
    Ford v. Freemen
  16. 19
    S.D. Tex.
    6 avg AI · 2 opinions
    AI 7
    0
    Doe v. Salesforce.Com, Inc.
  17. 20
    5th Cir.
    5 avg AI · 56 opinions
    AI 12
    0
    BP Exploration & Prodn, Inc. v. ID
  18. 21
    D.C. Cir.
    5 avg AI · 35 opinions
    AI 15
    0
    Save the Sound, Inc. v. FAA
  19. 22
  20. 23
    S.D. Fla.
    5 avg AI · 2 opinions
    AI 10
    0
    Compere v. Nusret Miami, LLC
  21. 24
    10th Cir.
    4 avg AI · 27 opinions
    AI 12
    0
    Trujillo v. Amity Plaza
  22. 26
    N.D. Ill.
    0 avg AI · 0 opinions
    AI 0
    0

Most AI-like opinions

The highest-scoring opinions in the dataset. On the real federal record almost none cross the flag line (18); these are simply the current leaders, shown with the signals that moved their score.

  • United Financial Casualty Co. v. Greg Ball
    Court of Appeals for the Fourth Circuit · Mar 30, 2023
    AI 50

    The text consists solely of repeated document metadata with no substantive legal content, indicating it is not a genuine judicial opinion.

    repeated document metadatalack of substantive content
    LLM 100Heuristic 0Confidence 20%
  • Petersen Energ�a; Eton Park v. Argentie Argentine Republic, YPF S.A.
    Court of Appeals for the Second Circuit · Mar 27, 2026
    AI 47

    The text contains malformed citations and potentially fabricated case names, indicating a high likelihood of AI assistance.

    malformed reporter citationsfabricated case names
    LLM 85Heuristic 12Confidence 18%
  • Perales v. Office of the Clerk
    District Court, District of Columbia · Jul 23, 2026 · Judge Jia M. Cobb
    AI 27

    The excerpt is a very short, standard dismissal order with no chatbot phrasing, buzzword clusters, citation issues, or structural AI tells, though its brevity limits confidence.

    Unusually uniform sentence rhythm
    LLM 2Heuristic 32Confidence 7%
  • United States v. Calvin Carter
    Court of Appeals for the Eighth Circuit · Jul 7, 2026
    AI 26

    The excerpt reads like a conventional concise appellate per curiam opinion with precise Guidelines and case citations, fact-specific reasoning, and no chatbot boilerplate, buzzword clusters, vague legal generalities, or malformed citation patterns suggestive of LLM drafting.

    Unusually uniform sentence rhythmChatbot-style holding recap
    LLM 5Heuristic 32Confidence 93%
  • Covington Specialty Insurance Company v. Omega Restaurant & Bar, LLC
    Court of Appeals for the Fourth Circuit · Jul 20, 2026
    AI 24

    The opinion largely reads like a genuine Fourth Circuit disposition with concrete record details, varied legal citations, and no chatbot boilerplate or buzzword clusters, though the anomalous citation year and section-numbering error create modest suspicion.

    Unusually uniform sentence rhythmone impossible/malformed Supreme Court citation: 598 U.S. 288 paired with year 2018section numbering jumps from III to VIotherwise precise case-specific facts and conventional appellate style
    LLM 22Heuristic 24Confidence 82%
  • United States v. Isaac Loggins, Jr.
    Court of Appeals for the Eighth Circuit · Jul 10, 2026
    AI 24

    The prose largely resembles a genuine Eighth Circuit opinion, but multiple concrete citation and internal-fact inconsistencies of the kind LLMs often hallucinate raise the likelihood substantially above baseline.

    fabricated or implausible Supreme Court citation to Rutherford v. United States, 146 S. Ct. 1320 (2026)wrong statutory citation to 28 U.S.C. § 944(a) for Sentencing Commission authorityinternal arithmetic inconsistency: 353-month sentence described as including 420 months of mandatory § 924(c) timecaption/venue inconsistency: appeals captioned from the Northern District of Iowa while footnote identifies one case from the Southern District of Iowaotherwise realistic judicial formatting and citation-heavy style with few chatbot buzzwords
    LLM 58Heuristic 2Confidence 78%
  • Rana v. Blanche
    Court of Appeals for the First Circuit · Jul 23, 2026
    AI 23

    The excerpt reads like a conventional appellate immigration opinion with precise citations, issue-specific legal analysis, and varied sentence structure, without chatbot framing, buzzword clusters, mechanical listicle scaffolding, or apparent citation hallucinations.

    Sparse citation density for opinion length
    LLM 6Heuristic 27Confidence 86%
  • Estate of Ismael Galvan Solorio v. Islamic Republic of Iran
    District Court, District of Columbia · Jul 21, 2026 · Magistrate Judge G. Michael Harvey
    AI 23

    The prose mostly resembles a genuine D.D.C. FSIA service opinion, but the repeated impossible dates and suspect future citations are strong hallucination-like signals that raise the likelihood of substantial AI assistance.

    multiple internal chronological impossibilitiesfuture or implausible case citationstypographical/legal-definition errors such as 'denies' for 'defines' and 'EECF'malformed or suspect pinpoint citationotherwise formal citation-heavy judicial style with few chatbot/buzzword tells
    LLM 58Heuristic 0Confidence 78%
  • Theis v. Intermountain Education Service District - Board of Directors
    Court of Appeals for the Ninth Circuit · Jul 21, 2026
    AI 22

    Although the text largely imitates authentic Ninth Circuit opinion style with plausible formatting and many precise citations, the notable citation-reference error and possible fabricated or malformed citations are strong AI-like tells alongside a somewhat mechanically structured analysis.

    citation inconsistency: “Id. at 967” follows a Dodge citation at page 778 but appears to refer to Johnsonpossible malformed citation: “3d. Cir.”future/possibly fabricated citations and docket detailstidy first/second analytical structuresome generic legal synthesis
    LLM 55Heuristic 1Confidence 77%
  • Iron Workers STL Pension Fund v. Barnhart Crane & Rigging Co.
    Court of Appeals for the Eighth Circuit · Jul 13, 2026
    AI 22

    The excerpt reads like a conventional Eighth Circuit opinion with precise procedural detail, plausible citations, varied sentence structure, and no chatbot framing, buzzword clusters, listicle scaffolding, or apparent citation hallucinations.

    Sparse citation density for opinion length
    LLM 6Heuristic 26Confidence 86%
  • Mark Lee v. West Virginia University Medical Corporation
    Court of Appeals for the Fourth Circuit · Jul 10, 2026
    AI 22

    The excerpt reads like a conventional appellate opinion with precise record and case citations, fact-specific procedural narration, varied sentence structure, and no chatbot boilerplate, buzzword clustering, listicle scaffolding, or citation irregularities suggestive of LLM drafting.

    Sparse citation density for opinion length
    LLM 3Heuristic 27Confidence 88%
  • American Academy of Pediatrics v. James Uthmeier
    Court of Appeals for the Seventh Circuit · Jul 8, 2026 · Leedissents
    AI 22

    The text reads like a routine appellate order and judicial dissent with precise, plausible citations, varied sentence structure, and no chatbot boilerplate, buzzword clustering, mechanical list structure, or vague uncited legal generalities.

    AI-favored vocabulary (foster)Chatbot-style hedging/boilerplate
    LLM 5Heuristic 26Confidence 88%
  • American Academy of Pediatrics v. James Uthmeier
    Court of Appeals for the Seventh Circuit · Jul 8, 2026
    AI 22

    The excerpt reads like a conventional appellate order and dissent with specific citations and natural judicial cadence, with only a minor formatting/case-number inconsistency and no strong generative-AI tells.

    AI-favored vocabulary (foster)Chatbot-style hedging/boilerplateprecise legal citationsvaried judicial sentence rhythmno chatbot framing or essay-style scaffolding
    LLM 8Heuristic 26Confidence 82%
  • United States v. Justin Schneider
    Court of Appeals for the Eighth Circuit · Jun 25, 2026
    AI 22

    Heuristic-only score (LLM judge unavailable).

    Chatbot-style hedging/boilerplate
    LLM 0Heuristic 22Confidence 30%
  • Carrozza v. CVS Pharmacy, Inc.
    Court of Appeals for the First Circuit · Mar 31, 2021
    AI 22

    The text exhibits characteristics of a genuine judicial opinion with precise citations, varied sentence structure, and no obvious AI-generated phrases or patterns.

    AI-favored vocabulary (foster)
    LLM 10Heuristic 33Confidence 90%
  • Forest View Rehabilitation and Nursing Center, LLC v. United States Small Business Administration
    Court of Appeals for the Seventh Circuit · Jul 20, 2026 · Easterbrook
    AI 20

    The text reads like a genuine appellate opinion with precise statutory and case citations, varied sentence rhythm, concrete factual/legal engagement, and no chatbot framing, buzzword clustering, mechanical structure, or citation anomalies suggestive of LLM drafting.

    Unusually uniform sentence rhythm
    LLM 5Heuristic 24Confidence 96%
  • Oak Lawn Respiratory and Rehabilitation Center v. United States Small Business Administration
    Court of Appeals for the Seventh Circuit · Jul 20, 2026 · Easterbrook
    AI 20

    The excerpt reads like a conventional appellate opinion with precise legal citations, varied sentence structure, case-specific factual engagement, and no chatbot framing, buzzword clusters, mechanical list structure, or citation anomalies suggestive of substantial LLM drafting.

    Unusually uniform sentence rhythm
    LLM 4Heuristic 24Confidence 93%
  • Parkshore Estates Nursing and Rehab Center v. United States Small Business Administration
    Court of Appeals for the Seventh Circuit · Jul 20, 2026 · Easterbrook
    AI 20

    The text reads like a genuine appellate opinion with precise statutory and case citations, varied sentence rhythm, concrete legal analysis, and no chatbot framing, buzzword clusters, mechanical list structure, or citation irregularities suggestive of LLM drafting.

    Unusually uniform sentence rhythm
    LLM 3Heuristic 24Confidence 94%
  • Forest View Rehabilitation and Nursing Center, LLC v. United States Small Business Administration
    Court of Appeals for the Seventh Circuit · Jul 14, 2026 · Easterbrook
    AI 20

    The text has precise legal citations, case-specific factual and statutory analysis, varied sentence rhythm, and a distinctive judicial voice without chatbot boilerplate, listicle structure, buzzword clusters, or citation anomalies.

    Unusually uniform sentence rhythm
    LLM 3Heuristic 24Confidence 96%
  • Oak Lawn Respiratory and Rehabilitation Center v. United States Small Business Administration
    Court of Appeals for the Seventh Circuit · Jul 14, 2026 · Easterbrook
    AI 20

    The text has precise and plausible legal citations, highly varied sentence rhythm, concrete statutory and factual analysis, and a distinctive judicial voice with no chatbot framing, listicle structure, buzzword clustering, or citation hallucination tells.

    Unusually uniform sentence rhythm
    LLM 3Heuristic 24Confidence 96%
  • Parkshore Estates Nursing and Rehab Center v. United States Small Business Administration
    Court of Appeals for the Seventh Circuit · Jul 14, 2026 · Easterbrook
    AI 20

    The text reads like a genuine appellate opinion with precise statutory and case citations, fact-specific reasoning, varied sentence rhythm, and no chatbot framing, buzzword clusters, mechanical list structure, or citation anomalies.

    Unusually uniform sentence rhythm
    LLM 3Heuristic 24Confidence 95%
  • Watson v. Republican National Committee
    Supreme Court of the United States · Jun 29, 2026 · Barrett
    AI 20

    Heuristic-only score (LLM judge unavailable).

    AI-favored vocabulary (foster)Heavy em-dash usageCitations to unrecognized reporters
    LLM 0Heuristic 20Confidence 30%
  • Graves-Buckingham v. Mayorkas
    District Court, District of Columbia · Jul 23, 2026 · Judge Jia M. Cobb
    AI 19

    The opinion otherwise reads like a human-drafted federal district court memorandum with detailed record citations and varied legal prose, but the facially implausible caption substitution is a notable anomaly that modestly raises concern.

    Sparse citation density for opinion lengthimplausible caption naming Markwayne Mullin as DHS Secretaryotherwise precise docket citations and case citationsvaried sentence rhythm with fact-specific legal analysisno chatbot framing or LLM buzzword clusters
    LLM 22Heuristic 17Confidence 78%
  • Savannah Byers v. Finishing Systems Inc
    Court of Appeals for the Third Circuit · Jul 20, 2026
    AI 19

    The text reads like a genuine, tightly edited appellate opinion with precise citations, varied sentence rhythm, judge-specific concise style, and no chatbot boilerplate, buzzword clustering, malformed citations, or vague essay-like filler.

    Sparse citation density for opinion length
    LLM 4Heuristic 23Confidence 93%
  • Keith Carnes v. Robert Blehm
    Court of Appeals for the Eighth Circuit · Jul 7, 2026
    AI 19

    The excerpt reads like a conventional Eighth Circuit opinion with precise procedural history, record-specific factual detail, standard legal framing, varied sentence structure, and properly formed citations, with no chatbot boilerplate, buzzword clustering, listicle scaffolding, or citation irregularities apparent.

    Unusually uniform sentence rhythm
    LLM 3Heuristic 23Confidence 95%