Novosibirsk, Russia

Novosibirsk State University

Novosibirsk State University is listed as QS 2026 rank =461. Novosibirsk State University has 6 source-backed AI policy claim records from 1 official source attribution. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.

Short answer

v1 public contract

Novosibirsk State University is listed as QS 2026 rank =461. Novosibirsk State University has 6 source-backed AI policy claim records from 1 official source attribution. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.

Citation-ready summary

As of this public record, University AI Policy Tracker lists Novosibirsk State University as an agent-reviewed AI policy record last checked on May 16, 2026 and last changed on May 16, 2026. The record contains 6 source-backed claims, including 6 reviewed claims, from 1 official source attribution. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/novosibirsk-state-university.json. The entity-level confidence is 92%. This tracker is not legal advice, not academic integrity advice, and not an official university statement unless the linked source is the university's own official page.

Claim coverage6 reviewedSource languageruPublic JSON/api/public/v1/universities/novosibirsk-state-university.json

Policy signals in this record

  • Evidence includes Academic integrity claims.
  • Evidence includes AI tool treatment claims.
  • Evidence includes Source status claims.
  • No specific AI service name is highlighted by the current public claim text.
  • Disclosure, acknowledgment, citation, or attribution language appears in the public claim text.
  • Teaching, assessment, coursework, or syllabus-related language appears in the public claim text.
Policy statusReviewed evidence-backed recordReview: Agent reviewedEvidence-backed claims6Reviewed6Candidate0Official sources1

This reference record summarizes visible public data only. Official sources and original-language evidence remain canonical; confidence is separate from review state.

This page is not legal advice, not academic integrity advice, and not an official university statement unless a linked source is the university's own official page.

Policy profile

Deterministic source-backed dimensions derived from this record's public claims.

Coverage score75/100Coverage labelbroad public coverageReview: Machine candidateAnalysis confidence74%

Policy profile rows are machine-candidate derived metadata. They are not final policy conclusions; inspect the linked claim evidence before reuse.

Analysis page-quality metadata is available at /api/public/v1/analysis/page-quality.json.

Policy presence

Novosibirsk State University has 1 source-backed public claim for policy presence; deterministic analysis status: unclear.

UnclearMachine candidateConfidence61%Evidence1Sources1

AI disclosure

Novosibirsk State University has 1 source-backed public claim for ai disclosure; deterministic analysis status: required.

RequiredMachine candidateConfidence77%Evidence1Sources1

Privacy and data entry

No source-backed public claim about privacy or data-entry restrictions is present in this profile.

The current public tracker record does not contain claim evidence about personal, confidential, sensitive, regulated, or student data entry into AI tools.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Approved tools

Novosibirsk State University has 1 source-backed public claim for approved tools; deterministic analysis status: allowed.

AllowedMachine candidateConfidence73%Evidence1Sources1

Named AI services

Novosibirsk State University has 1 source-backed public claim for named ai services; deterministic analysis status: allowed.

AllowedMachine candidateConfidence73%Evidence1Sources1

Teaching guidance

No source-backed public claim about teaching guidance is present in this profile.

The current public tracker record does not contain claim evidence about instructor, classroom, assessment-design, or syllabus guidance.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Research guidance

Novosibirsk State University has 1 source-backed public claim for research guidance; deterministic analysis status: recommended.

RecommendedMachine candidateConfidence77%Evidence1Sources1

Security and procurement

No source-backed public claim about AI security review or procurement is present in this profile.

The current public tracker record does not contain claim evidence about security review, procurement, vendor approval, risk assessment, authentication, SSO, or enterprise licensing.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Coverage score measures breadth of public, source-backed coverage only. It is not a policy quality, strictness, legal adequacy, safety, or compliance score.

Evidence-backed claims

6 reviewed evidence-backed public claim

Academic Integrity

The Department of Cytology and Genetics page says students may not present materials wholly created by a generative model, or minimally technically corrected by the student, as their own work.

Review: Agent reviewedConfidence92%

Normalized value: department_level_no_ai_as_own_work

Original evidence

Evidence 1
Нельзя представлять материалы, полностью созданные генеративной моделью или с минимальными техническими исправлениями от студента, как свою собственную работу.

Localized display only

Materials fully generated by a generative model, or minimally corrected by the student, cannot be presented as the student's own work.

Academic Integrity

For final qualification work and other assignments covered by the Department of Cytology and Genetics page, students are obliged to verify generated content and disclose generative-model use in a methods section or declaration.

Review: Agent reviewedConfidence91%

Normalized value: department_level_disclosure_required

Original evidence

Evidence 1
студент обязан: проверять достоверность любого контента, сгенерированного моделью; указывать факт использования генеративных моделей в разделе «Материалы и методы» или «Декларации об использовании генеративных моделей».

Localized display only

The page says the student is obliged to verify model-generated content and state use of generative models in Materials and Methods or a declaration.

Academic Integrity

The Department of Cytology and Genetics page says students remain responsible for originality, accuracy, authorship of ideas, and academic honesty when using generative models.

Review: Agent reviewedConfidence90%

Normalized value: department_level_student_responsibility

Original evidence

Evidence 1
студенты должны соблюдать принятые в научной среде этические нормы, поэтому ответственны за оригинальность и точность предоставляемых результатов, авторство идей и академическую честность своей работы.

Localized display only

Students are responsible for originality, accuracy, authorship of ideas, and academic honesty.

Academic Integrity

The Department of Cytology and Genetics page says final qualification works undergo Antiplagiat checking, including automatic detection of generated text fragments, and that such fragments may be grounds for not admitting a student to defense.

Review: Agent reviewedConfidence90%

Normalized value: department_level_generated_text_detection_risk

Original evidence

Evidence 1
Тексты выпускных квалификационных работ проходят обязательную проверку в системе «Антиплагиат», в которой есть этап автоматического выявления сгенерированных фрагментов текста. Наличие таких фрагментов в ВКР может послужить основанием для недопуска студента к защите своей работы.

Localized display only

Final qualification works are checked in Antiplagiat, including automatic detection of generated text fragments; such fragments may be grounds for non-admission to defense.

Ai Tool Treatment

NSU's Department of Cytology and Genetics says generative models may be used in final qualification work for idea inspiration, preliminary drafts with later revision, learning help, and routine technical tasks.

Review: Agent reviewedConfidence86%

Normalized value: department_level_permitted_uses

Original evidence

Evidence 1
Допустимо использование генеративных моделей в следующих ситуациях: для идейного вдохновения (например, мозгового штурма направления для решения задачи); для создания предварительных черновиков (с обязательной последующей доработкой); для помощи в обучении

Localized display only

The department lists permitted uses including idea inspiration, preliminary drafts with later revision, and learning support.

Source Status

This staged crawl found department-level NSU AI-use rules, but did not find a central NSU-wide binding policy for generative AI use in official-source discovery.

Review: Agent reviewedConfidence72%

Normalized value: department_level_source_found_no_central_policy_found

Original evidence

Evidence 1
Кафедра цитологии и генетики НГУ. Правила использования генеративных моделей (искусственного интеллекта) при подготовке ВКР.

Localized display only

The source identifies itself as an NSU Department of Cytology and Genetics page and frames the rules around final qualification work.

Candidate claims

0 machine or needs-review claim

Candidate claims are not final policy conclusions. They preserve source URL, source snapshot hash, evidence, confidence, and review state so the record can be audited before review.

Official sources

1 source attribution

Об использовании систем ИИ - Кафедра цитологии и генетики НГУ

cag.nsu.ru

Snapshot hash
0e80081ef4bd16f094c75f8fb5207629be2a0e0a5c5256a1826c3b24f1693149

Change log

Source-check timeline and diff-style claim/evidence preview.

View the public change record for this university, including source snapshot hashes, claim review states, and a diff-style preview of current source-backed evidence.

Last checkedMay 16, 2026Last changedMay 16, 2026Open change log

Corrections and missing evidence

Corrections create review tasks and do not directly change this public record.

If an official source is missing, stale, moved, blocked, or incorrectly summarized, submit a source URL, policy change report, or institution correction for review. Corrections must preserve source URLs, source language, original evidence, review state, and audit history.

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