Request for Peer Review - Properate Whitepaper

Lambda Science Inc. (DBA Properate) is in the process of publishing the largest remote energy rating study of its kind to date, involving nearly 7,000 homes. This study is presented in the format of a "Whitepaper", aiming to shed light on the accuracy of the green building software platform, Properate. A case study of performing remote home energy assessments is presented in that regard.

Lambda Science invites academic researchers to review this Whitepaper. Researchers agree to share their findings with Lambda Science. It is up to the researchers' discretion to publish their findings publicly; doing so is permissible by Lambda Science.

Due to the nature of the study and the aim of the Whitepaper, Lambda Science can only share limited info about the simulation and the underlying data. Researchers would not be able to access the underlying simulation technology nor would they be able to access input and output data. Lambda Science specifically requests Peer Review on the following items:

1. Do you agree with the Technology Review section ("White Box" to "Black Box" categorization) as it is presented?

2. How do you assess the applicability of the accuracy metrics Mean Bias Error (MBE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) to this study?

3. Do you agree with the methodologies employed for studying the data skew and error normalization?

4. Is the statistical significance/confidence presented in an understandable way?

No direct compensation is provided for the peer review to avoid potential biases; however, Lambda Science commits up to $2,500 of equal contribution to academia and industry consortiums for the peer review.

To access the Whitepaper you may use the below form. Please note that this form is only for researchers. The final version of the Whitepaper will be available to the broader audience at a later date.