High-resolution assessment of 20+ million EV registrations in 295 Chinese cities shows EVs use 30.9-212.8 MJ/100km less energy than ICE vehicles but with carbon intensities varying 18.2-270.4 gCO2/km, projecting emissions peak near 2030.
Does AI contribute to systemic risk reduction in non-financial corporations? Q
2 Pith papers cite this work. Polarity classification is still indexing.
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2025 2verdicts
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AI adoption proxies from text and patents improve out-of-sample distress prediction in Chinese firms when machine learning models use temporally pruned recent training windows.
citing papers explorer
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City-level energy and emission assessment based on 20+ million electric vehicle registrations in China
High-resolution assessment of 20+ million EV registrations in 295 Chinese cities shows EVs use 30.9-212.8 MJ/100km less energy than ICE vehicles but with carbon intensities varying 18.2-270.4 gCO2/km, projecting emissions peak near 2030.
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Forecasting financial distress in dynamic environments AI adoption signals and temporally pruned training windows
AI adoption proxies from text and patents improve out-of-sample distress prediction in Chinese firms when machine learning models use temporally pruned recent training windows.