System and method for deterministically generating reproducible evaluative scores for a subject of analysis

A system for generating reproducible evaluative scores for a subject of analysis, comprising:

• one or more processors;
• and
• a memory storing instructions that, when executed by the processors, cause the processors to:
• receive verified data describing the subject;
• store the verified source information in a fixed and version-controlled corpus, defining a static analytical context that maintains a known universe of evidence for evaluation;
• execute a large-language model (LLM) under a structured prompt framework that organizes evaluation questions, and directs a controlled scratch-pad reasoning process that records intermediate reasoning data representing extracted evidence and preliminary interpretations;
• perform a multi-pass deterministic analysis of the fixed corpus to produce structured, synthesized statements as reproducible evidentiary outputs;
• apply a rubric-based scoring engine that converts the synthesized statements into calibrated alignment scores within a defined numeric range and aggregates the scores to produce a composite score;
• and
• output the composite score and provenance metadata through an analytic interface.

A system for generating an evaluative score for a subject of analysis, comprising:

• one or more processors;
• and
• a memory storing instructions that, when executed by the processors, cause the processors to:
• receive data describing the subject from one or more information sources;
• store the data in a corpus for use during analysis;
• apply a large-language model to the corpus to extract information relevant to at least one evaluative criterion;
• generate one or more intermediate analytical outputs based on the extracted information;
• and
• produce, from the intermediate analytical outputs, an evaluative score representing an assessment of the subject.