Use Case
STEM Reasoning
PhD-level reasoning requires proof, not patterns.
The Problem
Where reasoning breaks down
Standard benchmarks reward correct final answers. Real STEM failures hide in the intermediate steps.
Correct-looking derivations with a single wrong step that invalidates the conclusion
Plausible answers that confuse related concepts, close enough to fool non-experts
Notation and convention errors that domain experts catch in seconds
How It Works
From silent errors to verified reasoning
BakeLens audits every reasoning step. Proof delivers PhD-verified data to close the gap.
BakeLens audits reasoning chains
Proof delivers verified expert reasoning
Graduate-level review of each reasoning step, not just the final answer
Step-by-step verified solutions from domain PhDs in bio, chem, math, med, physics, stats, finance
Classify errors: conceptual misunderstanding, procedural mistake, or notation error
Each step annotated with the reasoning principle it applies, not just the calculation
Map which domains and difficulty levels produce the most silent failures
Hard cases specifically targeting the error patterns diagnosis uncovered
What You Get
Deliverables
Reasoning Audit Report
Per-domain breakdown of error types, with example traces and severity ranking
PhD-Verified Datasets
Step-by-step expert solutions with provenance, including who verified it and why each step holds
Domain-Specific Eval Sets
Problems designed to catch the specific reasoning errors your model makes
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