Mathematical Statistics and Learning Template
Format your manuscript to the Mathematical Statistics and Learning requirements — abstract, a numbered style with alphabetical reference list (confirm in the guide) references, and required declarations — and submit through the journal's online submission system without a formatting rejection.
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How to Use the Mathematical Statistics and Learning Template | A Step-by-Step Guide
Authored by Sumalatha Gangadhar | Published on 19 August, 2026
Getting past the desk at Mathematical Statistics and Learning is usually less about the research and more about matching the journal’s exact submission rules. This template is built around MSL’s actual requirements — its abstract rules, a numbered style with alphabetical reference list (confirm in the guide) references, and the required declarations — so your submission clears screening on the first pass. Everything below tracks the MSL author guidelines; check it directly if anything looks out of date by the time you submit.
What is the Mathematical Statistics and Learning Template?
It’s a manuscript shell set up to MSL’s specifications for the mathematics of statistics and machine learning. Mathematical Statistics and Learning is published by EMS Press. The shell covers the title page, the abstract, a body in an introduction, the model and theory, results with proofs, and discussion order, and a reference list in a numbered style with alphabetical reference list (confirm in the guide) style.
What’s actually in a standard MSL submission:
Start with the title page (authors, affiliations, and ORCID iDs). The abstract is a concise abstract stating the main results. MSL also expects Mathematics Subject Classification (MSC) codes. The body follows an introduction, the model and theory, results with proofs, and discussion, and the reference list uses a numbered style with alphabetical reference list (confirm in the guide). Close with the declarations block: conflict of interest and funding.
What separates a clean submission from one that gets kicked back:
Beyond that, match your article type’s specific limits rather than assuming the defaults apply, keep a numbered style with alphabetical reference list (confirm in the guide) formatting consistent from the first draft, and submit only through the journal's online submission system — email submissions aren’t processed.
What does this Mathematical Statistics and Learning Template include?
The shell mirrors what MSL’s editorial staff check first: abstract format and length, a numbered style with alphabetical reference list (confirm in the guide) reference formatting, and a complete declarations block. For the journal’s full aims and scope, see the MSL journal home page. MSL offers an open-access option; check the current article-processing charge and any waiver before you commit. Manuscripts go in through the journal's online submission system, which also tracks your paper through peer review.
Steps to Use This Template with Scispace Agent
- Click Start Writing on this page — you land on the Scispace Agent prompt screen with the template already loaded.
- Use the loaded template as-is, or upload your own version if you have one.
- Edit the prompt with your actual details: topic, article type, and any word or figure limits specific to that type.
- Run it. The agent drafts directly into the correct structure — abstract, an introduction, the model and theory, results with proofs, and discussion body, figure placeholders, a numbered style with alphabetical reference list (confirm in the guide) references, and the full declarations block — with no manual reformatting afterward.
- Review the draft in View Outputs and regenerate any section that needs tightening.
- Export to Word or LaTeX once it’s ready for submission.
Mathematical Statistics and Learning Template Structure at a Glance
| Element | MSL requirement |
|---|---|
| Abstract | a concise abstract stating the main results |
| Main text | an introduction, the model and theory, results with proofs, and discussion |
| Declarations | Conflict of interest and funding |
| Figures / tables | Captioned, cited in order; check format and resolution rules in the guide |
| Supplemental | Large datasets, extra tables, code — uploaded separately and cited in text |
| Submission | the journal's online submission system |
Quick Tips for Using the MSL Template
Read the MSL author guidelines once before drafting and once before upload. Draft the abstract after your results are stable so it matches the paper. Set a numbered style with alphabetical reference list (confirm in the guide) as your reference style before adding a single citation — retrofitting it later is where errors creep in. Prepare Mathematics Subject Classification (MSC) codes early rather than leaving it to the end.
Best Practices
Skim two or three recent MSL papers to calibrate depth, structure, and figure style. State your contribution in the first two paragraphs, not on page ten. Write a data-availability statement that names a real repository rather than a placeholder, and disclose any preprint or conference version with identifiers in your cover letter. Confirm current open-access pricing and any institutional agreement before committing to a fee.
Before You Submit: Final Check
Do one focused pass against the MSL author guidelines: scope fit, abstract format, length, a numbered style with alphabetical reference list (confirm in the guide) references, required declarations, and figure quality. Then submit through the journal's online submission system.
