POLY-AIML-007: Machine Learning and Data-Driven Polymer Discovery

Master Prompt Guide and 16 Standardized Manuscript Prompts

SoftwareTheses automation-ready reference guide

Defining principle. A model becomes scientifically valuable only when its data integrity, generalization, uncertainty, chemical feasibility, and polymer-level validation are demonstrated.

How to Use This Guide

1.  Upload a literature matrix containing the relevant papers and extracted study information.

2.  Select one primary study branch and any justified conditional modules.

3.  Run the Master Prompt first to establish the evidence map, then run Prompts 1-16 in order.

4.  Retain exact placeholder numbering. Omit unsupported optional items or label them [INFORMATION REQUIRED].

5.  Complete the final claim-integrity audit before manuscript submission.