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α: calibrated so average coauthorship-adjusted count equals average raw count
Technological innovations in the materials and biological sciences ensure more consistent raw materials as production process inputs while IT improves material attribute discernment. When raw materials of two types are to be sorted, we provide a Bayesian information processing model with three parameters, one each to summarize product consistency, signals to discern raw material attributes, and incentives to correctly categorize materials. Consistency and discernment substitute when mis-categorization costs are symmetric. They can complement when mis-categorization into the prevalent type is heavily penalized. A single commodity market emerges whenever consistency is near 100 % but otherwise two may arise. A Catalyst Effect occurs whereby improvements in materials and biological technologies first increases demand for both discernment and consistency but then eliminates demand for discernment while further boosting demand for consistency.