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Jev Calibration Audit — n9omi
Independent audit repository testing whether Jev's probabilities are calibrated on EIA weekly petroleum reports, comparing Jev via LangChain TypeSafeClassifier against an LLM-as-classifier, rules, and climatology baselines.
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- Added
- Nov 2026
Highlights
- Checks calibration with reliability diagrams, ECE, Murphy decomposition, and the Spiegelhalter test.
- Compares Jev, an LLM-as-classifier via LangChain, rules, and climatology on identical questions.
- Ground truth comes from EIA weekly petroleum series, never from a model.
- Question types include Noul, Choice, and Score over horizons 0 and 1.
- Includes paired Brier/RPS differences, block-bootstrap CIs, and Diebold–Mariano tests.
Questions about this entry
Short answers drawn from the linked project or page.
Clone the repo, create a Python virtual environment, and run pip install -e .[jev,llm,dev]. An offline demo runs with synthetic data and no keys via jev-audit demo.
A real run needs EIA, TypeSafe, and LLM provider keys in .env. The offline demo uses synthetic data and requires no keys.
Each arm receives the same state text and typed questions from EIA-derived weekly states. For wpsr_text, you supply real EIA Weekly Petroleum Status Report highlights saved by week-ending date; dates are stripped by default.
It covers Noul yes/no, Choice, and Score questions. Horizon 0 tests current-week extraction and arithmetic; horizon 1 tests next-week draws and change buckets as forecasts.
Comparisons use paired loss differences on identical items, circular block-bootstrap confidence intervals, and Diebold–Mariano tests with Newey–West variance for autocorrelated weekly losses.
The repository is published under the GitHub account n9omi and runs as a Python package installed with pip in a virtual environment.
It is an independent audit on EIA weekly petroleum reports, not a universal evaluation of Jev. Its calibration results and recalibration maps apply to this domain and question bank, not all deployments.
Other listings of this project
Forks and copies of this project in the directory. This entry is the canonical one.
An unaffiliated, API-only audit of Jev calibration built on roughly 7,000 public HTTP calls, covering abstention, Korean, probabilistic coherence, option order, question interference, caching and latency, with a drift ledger.
Jev Practices & Patterns#community#jevbest#catalog-import
From the Jev guides
Original write-ups on what this entry is for.
From the Jev AI model community
Posts from builders shipping with Jev right now.