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    Machine Learning: Science and Technology

    Machine Learning: Science and Technology is Scopus-indexed (Q2, CiteScore 6.7), WoS SCIE, DOAJ. Published by Institute of Physics Publishing.

    Checked against the index lists dated 4 October 2026.

    ISSN 2632-2153Verify ISSN ↗

    Publisher: Institute of Physics Publishing

    Scopus · Q2WoS · SCIEOpen Access
    6.7
    CiteScore 2025
    Scopus
    Q2
    Best quartile
    rank 143 of 503 · 71st pctile
    3
    Indexed in
    major indexes

    Cost to publish: Checking DOAJ for article charges…

    ScopusElsevier Scopus
    Status
    Active
    Coverage
    2020–present
    Source type
    Journal
    Open access
    Yes
    CiteScore
    6.7
    SJR · SCImago
    0.872
    Q2 SJR quartile
    H-index
    48
    Best quartile
    Q2 · 71st pctile
    Subject areaRankPctileQ
    Software143 / 50371stQ2
    Artificial Intelligence166 / 57070thQ2
    Human-Computer Interaction73 / 19663rdQ2
    View this source on Scopus.com
    Web of ScienceClarivate (SCIE/SSCI/AHCI/ESCI)
    Collections
    SCIE
    Categories
    Computer Science, Artificial IntelligenceComputer Science, Interdisciplinary ApplicationsMultidisciplinary Sciences
    View this source on Web of Science Check JIF in JCR
    DOAJDirectory of Open Access Journals (live)
    Listed in DOAJ
    Open accessFully open access, peer reviewed

    Not listed in: ABDC, ABS / AJG, FT50, UT Dallas, ONOS (subscription), ONOS (APC covered)

    Quick answers

    Is Machine Learning: Science and Technology indexed in Scopus?

    Yes — actively indexed in Scopus, coverage 2020–present, best quartile Q2, CiteScore 6.7.

    What quartile is Machine Learning: Science and Technology in Scopus?

    Machine Learning: Science and Technology is Q2 in Software (rank 143 of 503), Q2 in Artificial Intelligence (rank 166 of 570) and Q2 in Human-Computer Interaction (rank 73 of 196), by CiteScore 2025.

    What is the impact factor of Machine Learning: Science and Technology?

    Machine Learning: Science and Technology is indexed in the Science Citation Index Expanded, so it may have a Journal Impact Factor in Clarivate's Journal Citation Reports. JCR is paid, so check it for the current value. The closest free measure is its Scopus CiteScore 6.7, which places it in quartile Q2 at the 71st percentile of its subject. Its SCImago Journal Rank (SJR, a free Scopus-based metric) is 0.872, quartile Q2, with an H-index of 48.

    How much does it cost to publish in Machine Learning: Science and Technology?

    The publisher lists an article processing charge of about US$3,000 for open access (source: OpenAlex). Many journals also publish by the subscription route at no cost to the author, so confirm on the journal's own website.

    Who publishes Machine Learning: Science and Technology and what is its ISSN?

    Machine Learning: Science and Technology is published by Institute of Physics Publishing. Its ISSN is 2632-2153.

    Is Machine Learning: Science and Technology in Web of Science?

    Yes — indexed in the Science Citation Index Expanded.

    Is Machine Learning: Science and Technology open access?

    Yes — it is an open-access journal, listed in DOAJ.

    How well cited is Machine Learning: Science and Technology? — open metrics via OpenAlex

    Machine Learning: Science and Technology has an h-index of 50 and a 2-year mean of 3.75 citations per paper (OpenAlex). Its Scopus CiteScore is 6.7, quartile Q2. On 2-year citations it ranks #113 of 371 Scopus journals in Software.

    50
    h-index
    3.75
    2-yr mean citations
    394
    i10-index
    1,488
    works indexed
    15,045
    total citations
    Publication fee · open access list price, US$
    US$3,000
    05001,0002,0003,000+
    2-yr mean citations, among Scopus journals in the same subject
    #113 of 371 Top 31% Software
    #155 of 407 Top 39% Artificial Intelligence
    #66 of 160 Top 42% Human-Computer Interaction
    Papers published per year
    02505002020: 137 papers13720202021: 112 papers11220212022: 96 papers9620222023: 200 papers20020232024: 344 papers34420242025: 316 papers31620252026: 283 papers so far2832026*

    Machine Learning: Science and Technology published 316 papers in 2025; its busiest recent year was 2024 with 344. 2026* is the year so far.

    Main topics
    Machine Learning in Materials ScienceModel Reduction and Neural NetworksQuantum Computing Algorithms and ArchitectureQuantum many-body systems

    h-index, i10-index and 2-year mean citedness are open, licence-clear metrics from OpenAlex — not a proprietary impact factor. The subject rank counts only journals that OpenAlex has a figure for; it is not a Scopus or Clarivate ranking. Updated 2026-10-14.

    Who publishes in Machine Learning: Science and Technology? — latest 96 articles, 2026

    In its latest 96 research articles (2026), authors are most often from United States (30.9%), China (15.1%) and Germany (10%).

    Author countriesUnited StatesUnited States30.9%ChinaChina15.1%GermanyGermany10%ItalyItaly6.6%FranceFrance6.3%United KingdomUnited Kingdom5.9% Most frequent institutions (papers)Massachusetts Institute of TechnologyMassachusetts Institute of Tech…5Chinese Academy of SciencesChinese Academy of Sciences5European Organization for Nuclear ResearchEuropean Organization for Nucle…4SLAC National Accelerator LaboratorySLAC National Accelerator Labor…4Sapienza University of RomeSapienza University of Rome3

    Countries are counted fractionally, so a paper by authors from two countries counts half to each.

    Are there integrity warnings for Machine Learning: Science and Technology? — indicators, not proof of misconduct

    Scopus status: Active. No retracted papers are recorded. The Problematic Paper Screener flags none of its papers. These are indicators to check, not findings against the journal.

    • Scopus statusActive
    • Retracted papers None recorded
    • Problematic Paper Screener flags None flagged

    Retractions from OpenAlex; flags from the Problematic Paper Screener (Cabanac, Labbé & Magazinov, CC BY), 2026-09-21 export. A flag marks a paper for a closer look; it is not a finding against the journal.

    Official sources & links

    Journal website ↗ Scopus source ↗ Web of Science ↗ DOAJ ↗ ISSN Portal · 2632-2153 ↗

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