Add: cost calc explanation

README.md

@@ -56,6 +56,10 @@ Its lightweight architecture enables fast, large-scale extraction of forecasts,
     <img src="https://huggingface.co/NOSIBLE/prediction-v1.1-base/resolve/main/plots/results.png"/>
 <p>
 
+Cost per 1M tokens for the LLMs was calculated as a weighted average of input and output token costs using a 10:1 ratio (10× input cost + 1× output cost, divided by 11), based on pricing from OpenRouter. This reflects the ratio between our prompt used to label our dataset.
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+For the NOSIBLE model, we conservatively used the cost of Qwen-8B on OpenRouter with a 100:1 ratio since the model produces a single output token when used as described in this guide. Despite this, our model is still the cheapest option.
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 ## Class token mapping.
 
 Because this is a classification model built off the [**Qwen3-0.6B**](https://huggingface.co/Qwen/Qwen3-0.6B), we mapped the `prediction` and `not-prediction` classes onto tokens. This is the mapping we chose.