Journal of Machine Learning for Modeling and Computing's 2026 Journal Metrics Score is 2.1, ranking Q2 in Statistical and Nonlinear Physics and 2 other subfields. Two-year citation average from OpenAlex data, updated August 2026.
Bookmark this page — track observed submission-to-acceptance timing, FWCI and field-normalized citation data for this journal in one view.
Journal Metrics Score 2026 · 2021–2024 window citedness 3.60.
Not available — there are not enough recent PubMed records with both received and accepted dates.
No journal-level APC is available in the current OpenAlex snapshot. Cost is excluded from scoring.
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Each spoke is a 0–100 percentile within a comparable journal cohort—not a percentage grade or a single black-box rating.
7 of 90 works · same type, year & subfield
2 works · same type, year & subfield
Below field-year expectation
of 512 topic-associated OpenAlex sources by lifetime output
FWCI compares papers with the same publication year, type, and field. 1.0 is the world average; above 1.0 is above expectation. This journal's median is 0.64, so its typical recent paper runs about 36% below its field benchmark.
7.8% of recent papers rank in the global top 10% after field normalization. This is easier to compare across specialties than raw citation totals.
Volume is separated from citation accumulation so newer papers are not presented as weaker simply because they are newer.
OpenAlex source records · 2020–2025
90 OpenAlex works · 2021–2024
OpenAlex topics show the research communities this journal serves.
Candidates share at least one OpenAlex subfield (or field, if too few do) with this journal's main research topics, ignoring generic catch-all topics, and are ordered by topic overlap, then current Journal Metrics Score.
* Cost is indicative only. APCs, taxes, waivers, and member discounts can change—always verify on the journal's official website.
| Category | Quartile |
|---|---|
| Statistical and Nonlinear Physics | Q2 |
| Artificial Intelligence | Q2 |
| Statistics, Probability and Uncertainty | Q2 |
A solid Q2 journal by citation data
By citation data, Journal of Machine Learning for Modeling and Computing is a solid journal: it is Q2 in Statistical and Nonlinear Physics and 2 other subfields, the second quarter of journals by score, and ranks #856 of 2,118 Computer Science journals by Journal Metrics Score (top 41%). Journal of Machine Learning for Modeling and Computing's 2026 Journal Metrics Score is 2.1. OpenAlex classifies its papers in subfields including Statistical and Nonlinear Physics, Artificial Intelligence, and Statistics, Probability and Uncertainty, so check that your topic fits its scope.
Verdict from citation data only: quartile and field rank by Journal Metrics Score (OpenAlex), publisher-reported acceptance rates, and PubMed submission and acceptance dates. See how we rank journals and how to verify indexing.
Confirm the exact title and ISSNs against the publisher homepage before a high-stakes submission decision.
Source: the current OpenAlex source record. OpenAlex works can include multiple work types. Fully Open Access is a source-level flag. Recent OA Works is summed from OpenAlex's counts_by_year series (up to the latest ten years); it is not a lifetime OA percentage. Any APC shown here is an indicative OpenAlex value—verify current charges on the journal's official website.
OpenAlex classifies Journal of Machine Learning for Modeling and Computing's papers in subfields including Statistical and Nonlinear Physics, Artificial Intelligence, and Statistics, Probability and Uncertainty. Read the aims and scope page and a few recent papers close to your topic before you prepare the manuscript.
Article types, word and figure limits, reference style, and the required statements (data availability, ethics, conflicts of interest, author contributions) are set by the journal. Prepare the cover letter and files to match them.
Use the submit link in Journal of Machine Learning for Modeling and Computing's author guidelines; Begell House runs the submission site. Every author usually needs an ORCID iD, and the corresponding author needs an account on the submission site.
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Journal of Machine Learning for Modeling and Computing does not publish an acceptance rate.
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See what the report coversBy citation data, Journal of Machine Learning for Modeling and Computing is a solid journal: it is Q2 in Statistical and Nonlinear Physics and 2 other subfields, the second quarter of journals by score, and ranks #856 of 2,118 Computer Science journals by Journal Metrics Score (top 41%). Journal of Machine Learning for Modeling and Computing's 2026 Journal Metrics Score is 2.1. OpenAlex classifies its papers in subfields including Statistical and Nonlinear Physics, Artificial Intelligence, and Statistics, Probability and Uncertainty, so check that your topic fits its scope.
Journal of Machine Learning for Modeling and Computing's 2026 Journal Metrics Score is 2.1, from the August 2026 data release. The score is a two-year citation average computed from OpenAlex (CC0) data: citations received in the most recent complete year to works published in the two prior years, divided by the number of those works.
We have not found an official acceptance rate published by Journal of Machine Learning for Modeling and Computing or its publisher, and Journal Metrics does not estimate one because submission counts are not public. To judge selectivity, compare Journal of Machine Learning for Modeling and Computing's quartile and score with similar journals, or ask the editorial office.
Journal of Machine Learning for Modeling and Computing's best quartile is Q2. By OpenAlex subfield: Q2 in Statistical and Nonlinear Physics; Q2 in Artificial Intelligence; Q2 in Statistics, Probability and Uncertainty. Quartiles rank journals by Journal Metrics Score within each subfield.
No. Journal Metrics computes the score independently from OpenAlex open data. Other providers use different citation databases, document types, and counting rules, so their published figures for Journal of Machine Learning for Modeling and Computing will not match this score exactly. Compare journals using one source at a time.
Comparable journals include Advanced Modeling and Simulation in Engineering Sciences, Data-Centric Engineering, Chaos, and Journal of Computational Science. Compare their scores, acceptance times, and costs in the recommended alternatives on this page before choosing where to submit.
Submit online through the link in Journal of Machine Learning for Modeling and Computing's author guidelines. Before submitting, check the scope, follow the author guidelines for article type, length, and required statements, and prepare a cover letter.