When Clarivate published the 2026 Journal Citation Reports on June 17, 2026, the release moved upward for most journals. In our June comparison of the two JCR editions, 19,208 titles had exact values in both releases: about three in five increased, roughly one in four declined, and the median rose from 1.8 to 1.9. Those numbers describe the JCR release itself and are reported here as editorial commentary.
Journal Metrics no longer displays Journal Citation Reports data. What follows instead is a look at the same journal landscape through the metric this site now computes and publishes: the 2026 Journal Metrics Score.
About the data on this page
Every chart and table below shows the Journal Metrics Score, which is computed from OpenAlex data and is not the Journal Impact Factor. The Journal Metrics Score is the two-year mean citedness of a journal, 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. Quartiles rank journals within each OpenAlex subfield by score.
Data source: OpenAlex (CC0)
The 2026 Journal Metrics Score landscape
Of 22,643 journals in the current dataset, 22,340 have a computable 2026 score. The median is 1.4 while the arithmetic mean is 2.18. That gap matters: a small number of exceptional values pull the mean upward, so the median is the clearer description of the typical journal.
Scored journals
22,340
Of 22,643 journal records
Median score
1.4
Middle half runs 0.5–2.7
Arithmetic mean
2.18
Sensitive to high outliers
90th percentile
4.8
Nine in ten journals score below this
How journals divide into subfield quartiles
Quartiles rank journals within each OpenAlex subfield by score, and each journal is labeled with the best quartile it reaches in any of its subfields. Because most journals belong to several subfields, the best-quartile view skews upward: 8,042 journals (36.0%) reach Q1 somewhere, which is why this chart should be read as “best placement,” not a strict 25/25/25/25 split.
| Quartile | Journals | Share |
|---|---|---|
| Q1 | 8,042 | 36.0% |
| Q2 | 6,051 | 27.1% |
| Q3 | 4,784 | 21.4% |
| Q4 | 3,390 | 15.2% |
| N/A | 73 | 0.3% |
Most journals score in the low single digits
Citation averages form a strongly right-skewed distribution, and the Journal Metrics Score is no exception. The largest group of journals scores below 1.0, and only 2.0% of scored titles reach 10.0 or higher. This shape is why comparing a raw score across unrelated fields says very little.
View distribution data
| Score range | Journals | Share |
|---|---|---|
| <1.0 | 8,601 | 38.5% |
| 1.0–1.9 | 5,380 | 24.1% |
| 2.0–2.9 | 3,326 | 14.9% |
| 3.0–4.9 | 2,967 | 13.3% |
| 5.0–9.9 | 1,628 | 7.3% |
| ≥10.0 | 438 | 2.0% |
The highest Journal Metrics Scores
Ranking by the 2026 score puts one journal far outside the rest of the distribution, so we show it separately to keep the common axis readable. Extreme values in any two-year citation average usually come from a very small publication denominator — a title that publishes few citable items while accumulating citations — and can also reflect quirks in the underlying OpenAlex source records. Treat the top of this list as a description of the metric, not a quality ranking.
Highest 2026 score · shown separately
Best subfield quartile: Q1
823.0
| Rank | Journal | 2026 Score | Best quartile |
|---|---|---|---|
| 2 | CA-A CANCER JOURNAL FOR CLINICIANS | 229.4 | Q1 |
| 3 | MMWR Recommendations and Reports | 120.2 | Q1 |
| 4 | MONOGRAPHS OF THE SOCIETY FOR RESEARCH IN CHILD DEVELOPMENT | 113.1 | Q1 |
| 5 | Radiologic Technology | 93.3 | Q1 |
| 6 | MMWR Surveillance Summaries | 52.6 | Q1 |
| 7 | CHEMICAL REVIEWS | 52.5 | Q1 |
| 8 | Signal Transduction and Targeted Therapy | 48.6 | Q1 |
| 9 | Electrochemical Energy Reviews | 42.4 | Q1 |
| 10 | NATURE REVIEWS MOLECULAR CELL BIOLOGY | 41.7 | Q1 |
| 11 | CHEMICAL SOCIETY REVIEWS | 41.0 | Q1 |
| 12 | International Journal of Educational Technology in Higher Education | 39.4 | Q1 |
Two widely searched journals
PLOS ONE and Scientific Reports illustrate where two large multidisciplinary journals sit in the score distribution. Their values come from the same canonical dataset as every chart above.
PLOS ONE
3.0
2026 Journal Metrics Score · best quartile Q1
Scientific Reports
4.8
2026 Journal Metrics Score · best quartile Q1
These are Journal Metrics Scores computed from OpenAlex data, not Journal Impact Factors; the two metrics use different source data and cannot be compared decimal-for-decimal.
What these scores do—and do not—mean
A higher Journal Metrics Score says that citations to a journal's recent works increased relative to its output. It does not tell you why that happened, whether your manuscript belongs there, or how often your eventual article will be cited.
- Compare journals within the same subfield before comparing raw values across fields.
- Use subfield quartiles when you need field-normalized context.
- Check scope, readership, indexing, fees, and author instructions alongside any metric.
- Remember that a two-year citation average is volatile for small journals.
- Choose for audience and manuscript fit first; use the score as supporting evidence.
Methodology and limitations
Source and inclusion
We analyzed the canonical Journal Metrics dataset for the August 2026 snapshot. A journal enters the analysis when it has a computable 2026 Journal Metrics Score; 303 records without a score were excluded.
The metric
The Journal Metrics Score is the two-year mean citedness of a journal, 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. Quartiles rank journals within each OpenAlex subfield by score.
Calculations
The mean is the arithmetic average; the median is the middle observation after sorting. Quartile shares use each journal's best quartile across its OpenAlex subfields.
Interpretive limits
This is a descriptive snapshot of one release across disciplines. It is not the Journal Impact Factor, cannot identify causes, and does not predict the influence of an individual paper.
Further reading
Journals newly receiving a score
Analyze the journals whose publication record is young enough that 2026 brings their first Journal Metrics Score.
The JCR 2026 release, explained
Editorial guide to the release naming, calculation context, and journal-selection workflow.
Understanding journal quartiles
Why Q1 through Q4 provide field context that a raw citation average cannot.
How impact factors are calculated
A step-by-step explanation of the classic two-year citation metric.
How to choose the right journal
Combine scope, audience, indexing, timelines, policies, and metrics.
Written by Dr. Meng Zhao
Physician-Scientist · Founder, LabCat AI
MD · Former Neurosurgeon · Medical AI Researcher
Dr. Meng Zhao is a former neurosurgeon turned medical-AI researcher. After years in the operating room, he moved into applied AI for clinical workflows and now leads LabCat AI, a medical-AI company working on decision support and research tooling for clinicians. He built Journal Metrics as a free resource for researchers who need reliable journal metrics without paid database subscriptions.
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