Tomsk, Russia

National Research Tomsk Polytechnic University

National Research Tomsk Polytechnic University has 2 source-backed AI policy claims from 2 official source attributions. Review state: agent reviewed; 2 reviewed claims. Last checked May 18, 2026.

National Research Tomsk Polytechnic University AI policy short answer

v1 public contract

National Research Tomsk Polytechnic University has 2 source-backed AI policy claims from 2 official source attributions, including 2 reviewed claims. The record review state is agent reviewed; original-language evidence snippets, source URLs, confidence, and public JSON are preserved for citation. Last checked May 18, 2026. Discovery context: National Research Tomsk Polytechnic University is listed as QS 2026 rank =688.

Citation-ready summary

As of this public record, University AI Policy Tracker lists National Research Tomsk Polytechnic University as an agent-reviewed AI policy record last checked on May 18, 2026 and last changed on May 18, 2026. The record contains 2 source-backed claims, including 2 reviewed claims, from 2 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/national-research-tomsk-polytechnic-university.json. The entity-level confidence is 83%. 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.

Policy signals in this record

  • Evidence includes Teaching claims.
  • Evidence includes Research claims.
  • No specific AI service name is highlighted by the current public claim text.
Policy statusReviewed evidence-backed recordReview: Agent reviewedEvidence-backed claims2Reviewed2Candidate0Official sources2

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 score45/100Coverage labelpartial public coverageReview: Machine candidateAnalysis confidence70%

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.

AI disclosure

No source-backed public claim about AI disclosure or acknowledgement is present in this profile.

The current public tracker record does not contain claim evidence about disclosing, acknowledging, citing, or declaring AI use.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Coursework

National Research Tomsk Polytechnic University has 1 source-backed public claim for coursework; deterministic analysis status: conditionally_allowed.

Conditionally AllowedMachine candidateConfidence71%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

Academic integrity

No source-backed public claim about academic-integrity treatment of AI use is present in this profile.

The current public tracker record does not contain claim evidence about AI use under academic integrity, misconduct, dishonesty, plagiarism, or cheating rules.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Approved tools

No source-backed public claim identifying approved or licensed AI tools is present in this profile.

The current public tracker record does not contain claim evidence that identifies institutionally approved, licensed, procured, or enterprise AI tools.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Named AI services

No source-backed public claim naming a specific AI service is present in this profile.

The current public tracker record does not contain claim evidence naming a specific AI service.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Teaching guidance

National Research Tomsk Polytechnic University has 1 source-backed public claim for teaching guidance; deterministic analysis status: recommended.

RecommendedMachine candidateConfidence71%Evidence1Sources1

Research guidance

National Research Tomsk Polytechnic University has 1 source-backed public claim for research guidance; deterministic analysis status: recommended.

RecommendedMachine candidateConfidence68%Evidence1Sources1

Security and procurement

National Research Tomsk Polytechnic University has 1 source-backed public claim for security and procurement; deterministic analysis status: required.

RequiredMachine candidateConfidence71%Evidence1Sources1

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

2 reviewed evidence-backed public claim

Teaching

TPU has an official continuing education program page titled Artificial Intelligence in Pedagogical Activity that describes teacher training in AI-supported lesson design, educational-data analysis, and evaluation of AI tools.

Review: Agent reviewedConfidence83%

Normalized value: official AI pedagogy professional development page

Original evidence

Evidence 1
Программа ориентирована на получение обучающимися практических навыков применения искусственного интеллекта в профессиональной деятельности преподавателя. В рамках программы обучающиеся освоят ключевые ИИ‑сервисы для образования, научатся проектировать занятия с использованием нейросетей, анализировать образовательные данные и оценивать эффективность ИИ‑инструментов.

Localized display only

The program says learners will gain practical skills applying AI in a teacher's professional work, including AI services for education, lesson design with neural networks, educational data analysis, and evaluation of AI tools.

Research

TPU's official research page presents digital technologies and artificial intelligence as a research direction, listing application areas such as hydrocarbons, nuclear technologies, power transmission, chemistry, biomedicine, pharmacology, and nondestructive testing.

Review: Agent reviewedConfidence80%

Normalized value: official AI research theme page

Original evidence

Evidence 1
Ученые ТПУ разрабатывают и внедряют цифровые технологии и искусственный интеллект в разных областях: Добыча и переработка жидких углеводородов; Ядерные технологии нового поколения; Передачи электроэнергии; Химия, биомедицина и фармакология; Неразрушающий контроль.

Localized display only

The page says TPU scientists develop and implement digital technologies and artificial intelligence in areas including hydrocarbons, nuclear technologies, power transmission, chemistry, biomedicine, pharmacology, and nondestructive testing.

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

2 source attribution

Цифровые технологии и искусственный интеллект

tpu.ru

Snapshot hash
81b1516e2fae82ac56cd67b40ebfad3bf45bd27833996862ea313e7d7a05c212

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 18, 2026Last changedMay 18, 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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