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How does shading analysis software accurately predict yearly production losses when sizing an off grid cabin power system with surrounding timber?

ChatGPTgpt-61 query11/1/2026
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Fan-out diagram

The searches the AI actually ran for this prompt.

SEED QUERY
How does shading analysis software accurately predict yearly production losses when sizing an off grid cabin power system with surrounding timber?
1 real search · 1 real-search pass
NREL SAM photovoltaic shading analysis tree shading horizon profile diffuse irradiance module mismatch annual energy production softwareGoogle ↗
OBSERVEDReason

Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.

Query classes

Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.

ChatGPT real searches (1)
Short factOther / navigationalComparisonConsequenceReason100%DefinitionInstructionYes / no

Classes come from the query-classifier (a local Laya model). 1 of 1 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.

Searches and sources

ChatGPT1 real searches · gpt-6
NREL SAM photovoltaic shading analysis tree shading horizon profile diffuse irradiance module mismatch annual energy production software Google ↗

Queries

1 queries · click a column to sort
Query / typeSearchIntentQuery classRouting formatClusterFreq ↓Weight
NREL SAM photovoltaic shading analysis tree shading horizon profile diffuse irradiance module mismatch annual energy production software
OBSERVED
Google ↗
AI Mode ↗
—Reason——1x
of 1