Skill UI

Molfeat is a Python toolkit that converts SMILES/RDKit molecules into embeddings via 100+ calculators, transformers, and pretrained models for QSAR, screening, similarity search, and deep learning pipelines.

Query UCSF’s ZINC22 repository of 230M+ purchasable compounds via the web UI or CartBlanche APIs to fetch IDs/SMILES, run similarity, supplier, or random sampling, and assemble docking-ready libraries for virtual screening.

Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. It enables pKa prediction, molecular docking, conformer search, and protein-ligand cofolding without local HPC infrastructure. Ideal for batch screening and multi-step chemistry pipelines in drug discovery.

This skill provides deep, cross-border financial analysis and valuation metrics for stocks across multiple markets (e.g., US, HK). Users can access detailed income statements, balance sheets, cash flow data, analyze business segments, compare valuation multiples (PE, PB), run sophisticated DCF models, and perform value screening. It is an essential tool for fundamental research, investment modeling, and corporate analysis.

This guide provides an in-depth understanding of the peer-review process for Conservation Biology, covering double-blind review standards, editorial screening criteria, and expert review priorities. It teaches authors how to structure their research to explicitly demonstrate conservation relevance, novelty, and transferable implications, effectively stress-testing a manuscript against common desk-rejection grounds.

This tool provides a comprehensive guide to the manuscript review process for Demography journal. It details the double-blind review structure, the mandatory pre-review desk screening (by Editor/Deputy Editor), and the common grounds for desk rejection. By stress-testing your paper against these academic standards, authors can significantly improve their work, ensuring methodological rigor and general interest before submission.

This guide provides a comprehensive, step-by-step walkthrough of the Journal of Econometrics (JoE) submission and review lifecycle. It covers the single-anonymized review structure, the crucial initial editor screening process, and details the three submission tracks (Regular, Annals, Themed). It also outlines the rigorous methodological criteria expected from modern econometric submissions, including the required elements for the initial editorial packet.

This guide details the rigorous review process for the Journal of Policy Analysis and Management (JPAM). It helps authors pre-empt potential objections—from desk screening to cross-disciplinary peer review—by detailing expected standards, article types, and the criteria for acceptance or rejection. Use this before submission to stress-test your manuscript and maximize acceptance chances.

This guide details the rigorous review process for papers in Mathematical Finance, covering single-blind peer review standards, from editor screening to line-by-line proof verification by referees. Learn what reviewers prioritize—methodological novelty, proof correctness, and financial applicability—to avoid common submission pitfalls and improve your chances of acceptance.

This comprehensive guide details the rigorous methodology for conducting systematic literature reviews and meta-analyses, particularly in educational research. It ensures the reproducibility and defensibility of the evidence corpus by documenting the entire PRISMA flow, from exhaustive multi-database searching and dual screening to structured data extraction and subsequent synthesis of findings.

A comprehensive guide for developing a rigorous, a-priori protocol for systematic reviews and meta-analyses in educational research. This tool ensures methodological transparency by defining the scope (PICO), eligibility criteria, search strategies, screening procedures, and synthesis plans before any data is collected, protecting the integrity of the research findings.

Provides a comprehensive, step-by-step workflow for conducting rigorous literature reviews across academic, biomedical, and technical domains. It guides users through defining research questions (PICO), developing systematic search protocols, evidence logging, source screening, structured data extraction, and synthesizing findings to build high-quality, reproducible review reports.