Chad Nash

Odyssey House

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 100%percentile

0Author DataRank

Indexed papers

0in pilot corpus

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Papers

Driven by 2 papers. Top paper: “Machine learning augmentation reduces prediction error in collective forecasting: development and validation across prediction markets with application to COVID events”.

Machine learning augmentation reduces prediction error in collective forecasting: development and validation across prediction markets with application to COVID events

eBioMedicine(2023)10.1016/j.ebiom.2023.104783

N/A

0.104DataRank · unranked

1 citations

Karl R Mattingly, Ellen Morwitch, Frederik Bossaerts, Manning Clifford, Chad Nash +3 more

Machine learning augmentation reduces prediction error in collective forecasting: development and validation across prediction markets

medRxiv(2023)10.1101/2023.01.19.23284578

N/A

0DataRank · unranked

0 citations

Karl R Mattingly, Ellen Morwitch, Frederik Bossaerts, Manning Clifford, Chad Nash +3 more