# SCI_EVAL_v3.1

Reasoning for
Scientific Discovery.

Verifying intelligence in high-stakes scientific domains. Our datasets and deterministic benchmarks provide the grounding required for advanced physics, formal mathematics, and biomedical research.

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acadify_sci_engine v3.1
// Init Formal Theorem Prover: Lean 4 await acadify.eval.math({ "theorem": "Fermat's Last Theorem (n=3)", "agent_url": "https://api.your-model.com/v1/chat" }); > Agent parsing axioms... [OK] > Agent generating derivation steps... [OK] > Synthesizing proof syntax... [OK] // Verifying with automated theorem prover const results = await acadify.eval.runLeanTests(); > Formal Verification: PASSED (Q.E.D)
12K+
Math Derivations
100%
Formally Verified
400+
GPQA Questions
PhD
Level Curation
TRAINING DATASETS

Post-Training for specialized scientific excellence.

High-fidelity SFT and RLHF data designed to drastically improve model reasoning in scientific domains where "close enough" is simply not an option.

Formal Mathematics

Step-by-step logical derivations formatted in Lean 4 and Coq. This dataset is heavily optimized for training frontier models in absolute mathematical precision and automated theorem proving.

# DATASET: MATH_FORMAL_V1

Chemical Synthesis

Multi-step reaction planning, molecule generation parameters, and property prediction data, meticulously curated and verified by PhD chemists for pharmaceutical drug discovery.

# DATASET: CHEM_SYNTH_L3

Physics-Informed Data

Training data rigorously filtered to respect thermodynamic conservation laws, quantum mechanics principles, and fluid dynamics, ensuring models ground outputs in absolute physical reality.

# DATASET: PHYSICS_CORE_v2
EVALUATION FRAMEWORKS

Scientific Benchmarks.

Measuring graduate-level reasoning and scientific accuracy with advanced zero-shot and deterministic chain-of-thought protocols.

GPQA Challenge

400+ graduate-level science questions designed to be strictly "un-googleable."

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MATH+ Harness

12,500+ competition-level mathematical problems requiring formal, step-wise proof verification.

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Scientific Evaluation Deliverables

  • Domain Accuracy Report

    Verified precision metrics across chemistry, physics, and biological test clusters.

  • Formal Proof Validation

    Deep-dive analysis of mathematical derivation flaws using automated theorem provers.

  • Optimization Roadmap

    Actionable instructions for improving SFT reasoning densities in mathematical modeling.

SUPPORT

Evaluation FAQ.

Understanding how we verify scientific accuracy and domain expertise in our STEM evaluation pipelines.

All STEM datasets undergo a rigorous multi-stage verification process. We combine domain-specific subject matter experts (PhDs in Physics, Chemistry, and Math) with automated formal verifiers like Lean and Coq to ensure absolute correctness before a single token is used for training.

Yes, we provide custom data generation pipelines for highly niche scientific domains such as quantum chemistry, specialized genomic research, and advanced fluid dynamics. Please reach out to our enterprise team for scoping.

The GPQA Challenge is a suite of over 400 graduate-level science questions designed to be extremely difficult and specifically "un-googleable." It tests a model's true reasoning capabilities and prevents memorization-based hallucination.

Absolutely. Our MATH+ Harness evaluates models on complex, competition-level mathematics problems, requiring step-by-step derivations that are subsequently verified by automated theorem provers like Lean 4.

Ready to benchmark your models?

Get immediate access to our graduate-level evaluation frameworks and scientific validation APIs.

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