Model Name: Smart Critical Appraisal (SCA) Version: 1.0 Overview Smart Critical Appraisal (SCA) is a large-language-model–assisted appraisal system designed to support structured quality assessment of included studies within systematic review workflows. Integrated directly into Nested Knowledge’s AutoLit platform, SCA helps reviewers evaluate methodological quality, risk of bias, and study reliability using established appraisal frameworks. The...
Model Name: Adaptive Smart Tags (AST) Version: 1.0 Overview Adaptive Smart Tags (AST) is a large-language-model–powered information extraction and recommendation system designed to support systematic literature reviews by identifying custom, user-defined concepts within study abstracts and/or full texts. Unlike Core Smart Tags (which address predefined fields such as PICO or study type), AST enables reviewers...
The Screening Model is a machine learning system designed to assist systematic review teams in prioritizing and screening literature records based on their likelihood of inclusion in a review. The model learns from screening decisions made within a specific nest, identifying patterns associated with included, excluded, or advanced records. It then generates inclusion or advancement probabilities for unscreened records. These probabilities can be used to: Assist manual screening workflows by prioritizing records based on predicted relevance, or Power the Robot Screener, an automated reviewer that can act as a second reviewer in dual screening workflows. The system is designed to accelerate the screening stage of evidence synthesis while maintaining a human-in-the-loop workflow.
Model Name: Smart Search Version: 1.0 Overview The Smart Search Tool leverages an agent-based large language model (LLM) system to generate optimized PubMed search queries tailored to specific research questions. It employs a generator-critic loop: This iterative process continues until the search meets predefined size and relevance criteria. Intended Use Training Data Evaluation Ethical Considerations...
Model Name: Research Question Refinement Version: 1.0 Overview The Research Question Refiner leverages LLMs to assist users in crafting research questions that meet the recommendations for systematic literature reviews (SLRs). The tool performs the following tasks: This iterative process helps users create research questions optimized for systematic review workflows. Intended Use Evaluation Ethical Considerations Limitations...
Model Name: PICO Hierarchy Generator Version: 1.0 Overview The Hierarchy Generator creates concept hierarchies from multiple research abstracts by extracting PICO entities and organizing them into meaningful relationships. The workflow involves: These hierarchies help users explore study characteristics, enabling better comprehension and synthesis of research evidence. Intended Use Evaluation Ethical Considerations Limitations Planned Improvements Contact...
Model Name: BioELECTRA-PICO Version: 1.0 Overview The BioELECTRA-PICO model (https://doi.org/10.18653/v1/2021.bionlp-1.16) is a variant of the ELECTRA architecture, specifically pre-trained and fine-tuned for extracting PICO elements (Participants, Interventions, and Outcomes) from biomedical research abstracts. This tool is used in systematic reviews and evidence-based medicine workflows to streamline information extraction and synthesis. Intended Use Training Data Evaluation...
Model Name: Smart Study Type (SST) Version: 1.0 Overview Smart Study Type (SST) is a machine-learning–based classification system designed to automatically identify and categorize biomedical study designs from article titles and abstracts. SST is part of the Core Smart Tags suite and supports systematic literature reviews (SLRs) by assigning hierarchical study type labels and providing...
Model Name: Smart Study Location Version: 1.0 Overview The Smart Study Location tool identifies the geographical location of a study based on textual information in bibliographic data, including country and city mentions in abstracts and titles, and affiliation details. It is designed to extract the study’s most relevant location Key features: For non-original research or...
Model Name: Smart Study Size Version: 1.0 Overview Smart Study Size is a heuristic-based algorithm designed to extract participant numbers from study abstracts. It extracts participant (experimental unit) counts using a three-phase approach: The output is a single numeric value representing the estimated participant count. Intended Use Training Data Evaluation Ethical Considerations Limitations Planned Improvements...
