> For the complete documentation index, see [llms.txt](https://docs.nested-knowledge.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.nested-knowledge.com/resources/cite-nested-knowledge.md). # Cite Nested Knowledge Learn how to cite Nested Knowledge in your publications. If you use **Nested Knowledge** in a published review, you'll want to cite your nest and describe your workflow. These details let readers assess and reproduce your methods. A nest records your search, screening, tagging, and extraction decisions. Linking to it lets readers examine your process. ### Citing Your Nest Link to your nest so readers can access your **Synthesis**. Open **Synthesis**, then copy the browser URL or select **Share** (:share-nodes:). {% hint style="warning" %} Your nest's Synthesis must be public in order to freely share the link. See [Set up Synthesis Outputs](/review-workflow/synthesis/set-up-synthesis-outputs.md). {% endhint %} Link to the full **Synthesis** or a specific page, such as **Qualitative Synthesis** or **Dashboard**.
The Synthesis Share button in the top navigation, highlighted with a red outline.

Select Share in Synthesis to copy a link to your nest.

In your paper, link to the nest directly. For example: "The full results are available on our **Synthesis** page: \[link to nest]." In your references or bibliography, we recommend: \[Author last names and initials], et al. \[Nest name]. Nested Knowledge. \[link to nest]. Accessed \[date]. For example: Kallmes KM, Kallmes KR, Holub K, et al. COVID-19 RCTs – Phase I. Nested Knowledge. . Accessed September 14, 2021. Journals use different reference formats. Include the nest name, **Nested Knowledge**, the link, and your access date. ### Describing Your Methods Name **Nested Knowledge** and describe its role in your methods. State any AI-assisted steps clearly. For a short mention, name the platform and the stages you used. For example: "We used **AutoLit** (Nested Knowledge, St. Paul, MN) for search, screening, and extraction, and **Synthesis** to visualize results." Add or remove stages to match your workflow. The company location is optional and depends on the journal. For a fuller description, adapt the template matching your workflow. Complete every bracketed field. #### Smart Nest An AI-assisted rapid review workflow.
Smart Nest method description A rapid review was conducted using **Smart Nest**, an AI-assisted workflow within the **Nested Knowledge** evidence synthesis platform (Nested Knowledge Inc., St. Paul, MN, USA). Following refinement of the research question, **Smart Nest** generated and executed an AI-assisted PubMed search with **Smart Search**, screening eligibility criteria through **Smart Screener** using **Criteria-Based Screening**, data extraction with **Adaptive Smart Tags**, and critical appraisal with **Smart Critical Appraisal**. A human reviewer reviewed and verified AI-generated extraction outputs for included studies. Verified findings were narratively summarized using **Smart Insights**. The review methodology and outputs were compiled into a dashboard for visualization and interpretation.
#### Targeted Literature Review (TLR) An AI-assisted targeted review with sampled human checks.
Targeted literature review method description A targeted literature review was conducted using the **Nested Knowledge** evidence synthesis platform (Nested Knowledge Inc., St. Paul, MN, USA). The review was guided by a predefined research question and targeted eligibility criteria developed to identify evidence relevant to the review objective. An AI-assisted search strategy was generated using **Smart Search**, which identifies search concepts, terms, and Boolean combinations from the predefined research question. It was executed in \[a connected literature database] through an application programming interface (API). Retrieved records were screened for eligibility at the title and abstract \[and full-text] level(s) using **Criteria-Based Screening**. **Smart Screener** filled one reviewer seat, alongside a second, human reviewer and a third, human adjudicator. Relevant data were extracted using **Adaptive Smart Tags** (**ASTs**). Tags are the core unit of data capture. Here, **ASTs** configured extraction data fields. A human reviewed the AI-generated screening decisions and extracted data. Following extraction, evidence from included studies was synthesized into an interactive **Dashboard** with tables, diagrams, and **Smart Insights**.
#### Systematic Literature Review With Dual Screening A systematic review with **Robot Screener** and human review.
Systematic literature review with dual screening method description A systematic literature review was conducted using the **Nested Knowledge** evidence synthesis platform (Nested Knowledge Inc., St. Paul, MN, USA). The review followed a predefined protocol. Literature searching was conducted in \[database(s)] from \[dates]. The search strategy was \[generated/developed/refined] using **Smart Search**, which generates search concepts, terms, and Boolean combinations from the research question. Following deduplication, retrieved records were screened at the title and abstract level using a dual screening workflow. **Robot Screener** filled one reviewer seat. A second, human reviewer and a third, human adjudicator completed the workflow. **Robot Screener** was initially trained on \[a minimum of 50 adjudicated records]. The adjudicator evaluated discordant decisions and made the final eligibility determination. Potentially eligible full-text articles were independently assessed by two human reviewers against the predefined eligibility criteria. Disagreements were resolved through discussion or adjudication by a third human reviewer, and reasons for exclusion were documented. Data were extracted from included studies using **Adaptive Smart Tags** (**ASTs**). Tags are the core unit of data capture. Here, **ASTs** configured extraction data fields. The extraction framework and tag-specific prompts were \[piloted and refined on # studies] before full implementation. A human reviewer checked all AI-generated extraction outputs against the source publication before synthesis. Included-study data were displayed in the **Synthesis** **Dashboard**, using structured tables and figures. **Smart Insights** generated narrative summaries from data extracted through **ASTs**. A human reviewer \[reviewed/edited/approved] the summaries and checked them against the underlying evidence.
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