General information

Organisation type
University
ROR
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Research metrics

The calculation window differs from metric to metric: some cover the reporting year, others the whole history of the organisation. Which is which is set out in “Where these numbers come from” below. Recalculation is scheduled, once a day at night.

No data for 11 metrics Average KZ-SJR, Publications, Citations, Average Impact Factor, h-index and 6 more Show how they are calculated Collapse the list

These values have not been calculated for this university yet. How each metric is calculated and what data it needs:

  • Average KZ-SJR

    Average KZ-SJR across the university's journals; used in the university ranking.

    Methodology : Average KZ-SJR

  • Publications

    Number of the university's publications in the reporting year — articles with at least one author affiliated with the university in that year. Each article counts once; removed records and articles whose publication year is only estimated are excluded. An absolute count: it is not divided by staff size.

    Methodology : Publications

  • Citations

    Total citations received by all of the university's publications over the period.

    Methodology : Citations

  • Average Impact Factor

    Average Impact Factor across the university's publications.

    Methodology : Average Impact Factor

  • h-index

    The largest number h such that h publications have each been cited at least h times.

    Methodology : h-index

  • Q1 share

    Share of the university's publications that appear in Q1 journals of their subject subfield.

    Methodology : Q1 share

  • International co-authorship

    Share of publications with at least one foreign-affiliated co-author (P_intl ÷ P_total × 100). Source: Crossref/OpenAlex affiliations.

    Methodology : International co-authorship

  • Inter-university collaboration

    Share of the university's publications for the reporting year that have a co-author affiliated that same year with another Kazakhstani university. Advisory indicator: it does not enter the ranking's final score.

    Methodology : Inter-university collaboration

  • Partner universities

    Number of distinct other Kazakhstani universities that co-authored with the institution in the reporting year's publications — the breadth of collaboration. Advisory indicator: it does not enter the ranking's final score.

    Methodology : Partner universities

  • Citations per researcher

    Total citations to the university's articles divided by its staff headcount (citations per researcher). Computed only when the administrator-entered staff count is known; universities without it are not ranked on this lens rather than scored as zero.

    Methodology : Citations per researcher

  • Grant activity

    Composite of grant activity: funding volume (weight 0.5), grants won (0.3), active grants (0.2). Each component is normalised across all organisations; a component left blank is dropped and the remaining weights are renormalised. An entered zero is data and does take part in the calculation.

    Methodology : Grant activity

Grant activity

No data

Methodology

Where these numbers come from

Not a single number on this page was entered by hand at random. Each one is collected from external sources, matched by identifiers, verified and computed by a fixed formula. An organisation brings a difficulty a journal does not: the same affiliation is written a dozen different ways across sources. Below is the whole path, including what we do not know and where we get it wrong.

Sources

A university’s metrics are collected from external databases and from data the university itself submits. Each source is enabled separately and has its own harvesting schedule:

  • OpenAlex — publications, citations, affiliations
  • Crossref — article metadata and reference lists
  • ORCID — researchers and their achievements
  • ROR — the registry of organisations
  • University-supplied data — staff headcount and grants

Some details do not come from harvesting: editorial offices fill in individual fields, administrators enter and correct data, and file upload is supported. Such records go through the same matching and confidence rules, but do not count as an external source.

Calculation window

The h-index covers the organisation’s entire history; publications, citations, the Q1 share, international co-authorship and grant activity cover the calculation year. The scheduled recomputation runs once a day during the night hours, and public values do not change between runs.

Verification

Affiliations are matched by the organisation identifier and, where there is none, by the normalised name; duplicate organisations are merged rather than discarded. Every record gets a confidence score from 0 to 100, and records below the threshold do not enter the metric calculation.

Manual corrections

Staff headcount and grant components are entered by the university’s administrator. The platform’s editors may correct a computed value when the source data is plainly wrong; such a value is always flagged, and the flag is shown next to it.

The data path

Five steps from someone else’s record of an article to the number on this page. Step two is where organisations go wrong most often.

  1. 1

    Harvesting. Records of articles, references, authors and organisations are pulled from external sources on a schedule. The source of every record is stored with it.

  2. 2

    Resolving affiliations. An affiliation string is matched to an organisation by identifier and, where there is none, by the normalised name in three languages. Unresolved strings are queued rather than attributed to a similar organisation.

  3. 3

    Normalisation. Subjects, author names and organisation names are mapped onto the reference lists. The Kazakh, Russian and English forms of a name are linked to one another.

  4. 4

    Scoring. Every record gets a confidence score from 0 to 100 based on field completeness, agreement between sources and the age of the record. Below the threshold a record does not enter the calculation.

  5. 5

    Computation. The metrics are normalised across the cohort of universities and combined into a score using the weights in the table below. The result is published together with its calculation window, sources and confidence.

Weights of the final score

The same thing that opens under “How it is calculated” on each metric, gathered into one table. The weights are fixed: recomputing with new weights counts as a new edition of the methodology and is dated. A metric that could not be computed for an organisation is dropped along with its weight and the rest are renormalised — it is not replaced by a zero.

Metrics behind the final score: what exactly is counted and the weight
Metric What exactly is counted Weight
Average KZ-SJR The mean KZ-SJR of the journals the university’s articles appeared in, weighted by the number of articles 22
h-index The largest h for which there are h publications cited at least h times each 18
Q1 share The share of articles published in first-quartile journals of their field in the year of publication 13
Citations References to the organisation’s articles, excluding those coming from retracted works 12
Publications Articles carrying the organisation’s affiliation, after duplicates are removed 8
Average Impact Factor The mean impact factor of the journals the articles appeared in, weighted by the number of articles 8
Citations per researcher Citations divided by the staff headcount; without a headcount it is not computed 8
Grant activity Funding 0.5, grants won 0.3, active grants 0.2, with renormalisation 6
International co-authorship The share of articles whose affiliations include an organisation outside Kazakhstan 5

The data quality behind every number

Confidence is a service score of our data about an object, not an expert judgement of the object itself. A low value means the sources disagree with each other, mandatory fields or identifiers are missing, or the data came from a low-trust source.

The platform reconciles differences between sources regularly: critical fields and the metrics that form the ranking at least once a week, less sensitive reference data at least once a month. A small discrepancy is only logged; a significant one creates a manual review task with an assigned owner.

You can report an error in the data through the feedback form: the request enters the tracking system and is followed through to a reply to the person who sent it.

Full methodology Report a data issue

The methodology changes by versions: each has an effective date, and earlier values are never rewritten retroactively.

Specialization areas

Specialization: Not yet confirmed

Based on 15 classified publications

Engineering

5 publications Confidence: 88 out of 100

Correct the name

Medicine

4 publications Confidence: 91 out of 100

Correct the name

Economics, Econometrics and Finance

2 publications Confidence: 100 out of 100

Correct the name

Health Professions

1 publication Confidence: 48 out of 100

Correct the name

Immunology and Microbiology

1 publication Confidence: 100 out of 100

Correct the name

Biochemistry, Genetics and Molecular Biology

1 publication Confidence: 45 out of 100

Correct the name

Social Sciences

1 publication Confidence: 96 out of 100

Correct the name

Leading researchers

Researchers the organisation’s administrator marked as recommended come first; the rest follow by h-index. Achievements are collected from ORCID and OpenAlex, each with its own confidence score.

  • Khurshid Ahmad

    h-index: 3 ORCID

    Achievements

    • Korean Society for Molecular and Cellular Biology (2016) Membership ORCID Confidence: 60 out of 100
    • h-index: 40 OpenAlex Confidence: 60 out of 100
    • i10-index: 87 OpenAlex Confidence: 60 out of 100
    • 2-year mean citedness: 43.47 OpenAlex Confidence: 60 out of 100
    • Total citations: 6,799 OpenAlex Confidence: 60 out of 100
    • Works count: 154 OpenAlex Confidence: 60 out of 100

    Key publications

    • MuSC cultivation for cultured meat production: recent advances, current limitations, and future directions Confidence: 60 out of 100
    • Alginate-derived smart hydrogel dressing with CaP/ZnO synergy for on-demand hemostasis and pH-triggered curcumin delivery Confidence: 60 out of 100
    • Terpenoids: A Comprehensive Review on Biosynthesis, Applications and Enhancement Strategies for Translational Research Confidence: 60 out of 100
    • The Gut-Mammary Axis in Dairy Cattle: A Review of Gut Microbiota-Driven Influences on Lactation Confidence: 60 out of 100
    • Phytochemical Profiling, In Vitro α-Amylase Inhibitory and Antioxidant Activities of Madhuca longifolia Leaf and Bark Extracts with Molecular Docking Analysis Confidence: 60 out of 100
    • Burden of 375 diseases and injuries, risk-attributable burden of 88 risk factors, and healthy life expectancy in 204 countries and territories, including 660 subnational locations, 1990–2023: a systematic analysis for the Global Burden of Disease Study 2023 Cited 890 times Confidence: 60 out of 100
    • Global burden of 292 causes of death in 204 countries and territories and 660 subnational locations, 1990–2023: a systematic analysis for the Global Burden of Disease Study 2023 Cited 578 times Confidence: 60 out of 100
    • Mechanistic Insights into the Antimicrobial Actions of Metallic Nanoparticles and Their Implications for Multidrug Resistance Cited 510 times Confidence: 60 out of 100
    • Binding of Tolperisone Hydrochloride with Human Serum Albumin: Effects on the Conformation, Thermodynamics, and Activity of HSA Cited 271 times Confidence: 60 out of 100
    • Computer Aided Drug Design: Success and Limitations Cited 424 times Confidence: 60 out of 100

  • Yongcheng Jin

    h-index: 1 ORCID

    Achievements

    • h-index: 33 OpenAlex Confidence: 60 out of 100
    • i10-index: 97 OpenAlex Confidence: 60 out of 100
    • 2-year mean citedness: 8.89 OpenAlex Confidence: 60 out of 100
    • Total citations: 4,078 OpenAlex Confidence: 60 out of 100
    • Works count: 181 OpenAlex Confidence: 60 out of 100

    Key publications

    • Dual Anion‐Involved Interfacial Chemistry Enables Ultra‐Stable PEO‐Based Solid‐State Lithium Metal Batteries by Suppressing NMP‐Induced Side Reactions Confidence: 60 out of 100
    • Bulk-surface engineering of PEO-based electrolytes via controlled [NMP-Li+] coordination for room-temperature quasi-solid-state lithium metal batteries Confidence: 60 out of 100
    • Trilayer Topological Structure with Ni/Mn Concentration Gradient for High‐Performance Cobalt‐Free Lithium‐Rich Oxide Cathode with Enhanced Anionic Redox Reaction Confidence: 60 out of 100
    • Hydrogen Evolution in Lithium Water-in-Salt Electrolytes Confidence: 60 out of 100
    • CeO2-modified LiCoPO4 cathodes with enhanced high-voltage and low-temperature performance enabled by graphitic carbon coating and lattice engineering for lithium-ion batteries Confidence: 60 out of 100
    • Liquid‐State Templates for Constructing B, N, Co‐Doping Porous Carbons with a Boosting of Potassium‐Ion Storage Performance Cited 178 times Confidence: 60 out of 100
    • Solid Polymer Electrolyte Based on Polymerized Ionic Liquid for High Performance All-Solid-State Lithium-Ion Batteries Cited 121 times Confidence: 60 out of 100
    • Micron-sized monocrystalline LiNi 1/3 Co 1/3 Mn 1/3 O 2 as high-volumetric-energy-density cathode for lithium-ion batteries Cited 127 times Confidence: 60 out of 100
    • Improving the Li-ion conductivity and air stability of cubic Li7La3Zr2O12 by the co-doping of Nb, Y on the Zr site Cited 143 times Confidence: 60 out of 100
    • Preparation and evaluation of high lithium ion conductivity Li 1.3 Al 0.3 Ti 1.7 (PO 4 ) 3 solid electrolyte obtained using a new solution method Cited 141 times Confidence: 60 out of 100

  • Wei Liu

    h-index: 1 ORCID

    Achievements

    • h-index: 24 OpenAlex Confidence: 60 out of 100
    • i10-index: 45 OpenAlex Confidence: 60 out of 100
    • 2-year mean citedness: 4.42 OpenAlex Confidence: 60 out of 100
    • Total citations: 1,729 OpenAlex Confidence: 60 out of 100
    • Works count: 93 OpenAlex Confidence: 60 out of 100

    Key publications

    • preparation of nanosized MnO Confidence: 60 out of 100
    • The Effect of Microplastics on the Bioenergetics of the Mussel Mytilus coruscus Assessed by Cellular Energy Allocation Approach Cited 92 times Confidence: 60 out of 100
    • Stability and surface properties of selenium nanoparticles coated with chitosan and sodium carboxymethyl cellulose Cited 80 times Confidence: 60 out of 100
    • Interaction of silver nanoparticles with antioxidant enzymes Cited 107 times Confidence: 60 out of 100
    • DNA damage and oxidative stress induced by CeO2nanoparticles in human dermal fibroblasts: Evidence of a clastogenic effect as a mechanism of genotoxicity Cited 78 times Confidence: 60 out of 100
    • Protein corona formation for nanomaterials and proteins of a similar size: hard or soft corona? Cited 158 times Confidence: 60 out of 100

Partners for international projects

Universities with a similar research profile, ranked with a bonus for cross-border collaboration. Advisory only.

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International ranking crosswalk

This is RankScience data arranged in the structure of the international ranking — not official ranking scores.

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