# Market Thesis Research Bundle

Question: Given the AI data-center power crunch, will gas turbine and distributed-generation suppliers show data-center-driven orders becoming a material share of backlog rather than a one-off pipeline story?

What this bundle is: a reasoning and monitoring scaffold. It organizes public evidence into observations, claims, uncertainty branches, thresholds, and a watch plan.

What this bundle is not: primary evidence, live market data, trade advice, or a substitute for official, live, or current web sources.

Core tension: Given the AI data-center power crunch, will gas turbine and distributed-generation suppliers show data-center-driven orders becoming a material share of backlog rather than a one-off pipeline story?

Current inference to verify: {'stance': 'mixed_yes', 'confidence': 'medium', 'summary': 'Current evidence supports a real conversion from AI data-center power demand into multi-quarter orders and backlog growth at leading gas-turbine and grid-adjacent suppliers, but public disclosures still do not consistently prove that data-center work is a material backlog share across the broader distributed-generation supplier set.', 'inference_boundary': 'This is a current inference to verify from disclosures and awards, not a prediction signal.'} Treat this as a hypothesis that must be refreshed against live official sources, not as a signal.

How to use: read `source_priority.json` first, refresh sources in `live_verification_plan.json`, then use `fact_inference_split.json`, `thresholds.json`, and `watch_schedule.json` to decide what changed. Do not infer buy/sell/hold, position sizing, execution, or asset-price direction from this artifact.