Machine Learning with Applications Template 2026
Get your Machine Learning with Applications paper right the first time: a ready-made structure with the right abstract and citations, so editors see your science, not formatting slips.
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How to Use the Machine Learning with Applications Template | A Step-by-Step Guide
Authored by Sumalatha Gangadhar | Published on 26 August, 2026
Submitting to Machine Learning with Applications goes smoothly when your draft already matches the journal's own rules. Editors screen new manuscripts against the Machine Learning with Applications guide for authors before peer review, so formatting, structure, and required statements should be right on the first draft rather than repaired during upload. This template sets that structure up for you.
What is the Machine Learning with Applications Template?
It is a manuscript shell aligned to Machine Learning with Applications. It covers front matter, the abstract the journal expects, a body organized to the journal's article types, and a reference list in the journal's required style. Confirm current scope and article types on the Machine Learning with Applications journal page before you draft.
What's actually in a Machine Learning with Applications submission:
Prepare the title, authors, affiliations, and ORCID iDs. Write the abstract to the journal's rule and word limit, organize the body to the article type, and apply the required reference style from the first citation. Complete every declaration (ethics, competing interests, funding, data availability) the Machine Learning with Applications guide for authors lists, and cite figures and tables in order.
What separates a clean submission from one that gets kicked back:
The common failure modes are formatting or reference style that does not match the guide for authors, missing required statements, and an incomplete portal checklist. Clear all three against the Machine Learning with Applications guide for authors before you submit.
What does this Machine Learning with Applications Template include?
The shell mirrors what editorial staff check first: article-type fit, the abstract rules, required declarations, and the journal's reference style. For more detail see the author resources. When your draft is ready, upload it through Editorial Manager.
Steps to Use This Template with SciSpace Agent
- Click Start Writing on this page. The SciSpace Agent prompt screen opens with the template loaded.
- Use the loaded template, or upload a version your group already uses for Machine Learning with Applications.
- Edit the prompt with your topic and article type, and note any requirement from the Machine Learning with Applications guide for authors.
- Run the prompt. The agent drafts into the correct structure and reference style.
- Use View Outputs to verify required statements and formatting are present.
- Export and submit through Editorial Manager.
Machine Learning with Applications Template Structure at a Glance
| Element | Machine Learning with Applications requirement |
|---|---|
| Abstract | The guide does not specify a structured or unstructured format or headings by article type. Authors must provide a concise and factual abstract not exceeding 250 words, briefly stating the purpose of the research, principal results, and major conclusions. The abstract should stand alone; references should be avoided (if essential, cite author(s) and year(s)), and non-standard or uncommon abbreviations should be avoided or defined at first mention |
| Main text | No overall main-text word or page limit is stated. Technical notes are limited to a maximum of 10 pages. For article structure, the manuscript should be divided into clearly defined and numbered sections (subsections 1.1, then 1.1.1, etc.); no article-type-specific section order is prescribed. The guide separately describes theory and calculation sections, and requires acknowledgements in a separate section directly before the reference list |
| Declarations | Ethics approval/consent as applicable; competing interests; funding; data availability |
| Figures/tables | Publication-ready; cited in order |
| Supplemental | Upload separately when used |
| Keywords | Provide 1 to 7 keywords for indexing. Keywords must be in English; the guide asks authors to avoid keywords consisting of multiple words (using 'and' or 'of') and recommends using abbreviations only when firmly established in the field. No MeSH requirement is stated |
| References | American Psychological Association (APA), Seventh Edition (2020) citation style. The reference list is arranged alphabetically and then chronologically; same-author references in the same year use 'a', 'b', 'c', etc. after the year. DOI links are encouraged |
| Peer review | Single-anonymized review process (single-blind); submissions deemed suitable are typically reviewed by a minimum of two reviewers for an independent expert assessment |
| Submission | www.editorialmanager.com/mlwa/default.aspx |
Quick Tips for Using the Machine Learning with Applications Template
Read the Machine Learning with Applications guide for authors once before drafting and once before upload. Draft the abstract after results are stable. Set the reference style before adding citations. Keep a cover letter that states your contribution and fit to Machine Learning with Applications in under a page.
Best Practices
Skim two or three recent Machine Learning with Applications papers to calibrate depth and figure style. Make the novelty clear in the first two pages. Deposit data and code when the policy on the Machine Learning with Applications journal page requires it. Disclose any preprint or conference version with identifiers in the cover letter.
Before You Submit: Final Check
Do one focused pass against the Machine Learning with Applications guide for authors: scope, length, reference style, required declarations, and figure quality. Then submit through Editorial Manager.
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