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77,272
Phylogenetic identification and in situ detection of individual microbial cells without cultivation. Microbiol. Rev
, 1995
"... cultivation.of individual microbial cells without Phylogenetic identification and in situ detection ..."
Abstract
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Cited by 1070 (29 self)
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cultivation.of individual microbial cells without Phylogenetic identification and in situ detection
On Bayesian analysis of mixtures with an unknown number of components
- INSTITUTE OF INTERNATIONAL ECONOMICS PROJECT ON INTERNATIONAL COMPETITION POLICY," COM/DAFFE/CLP/TD(94)42
, 1997
"... ..."
Monitoring the future: National survey results on drug use
- I: Secondary school students (NIH Publication No. 05-5726). Bethesda, MD: National Institute on Drug Abuse
, 2005
"... by ..."
On the time course of perceptual choice: the leaky competing accumulator model
- PSYCHOLOGICAL REVIEW
, 2001
"... The time course of perceptual choice is discussed in a model based on gradual and stochastic accumulation of information in non-linear decision units with leakage (or decay of activation) and competition through lateral inhibition. In special cases, the model becomes equivalent to a classical diffus ..."
Abstract
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Cited by 457 (20 self)
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diffusion process, but leakage and mutual inhibition work together to address several challenges to existing diffusion, random-walk, and accumulator models. The model provides a good account of data from choice tasks using both time-controlled (e.g., deadline or response signal) and standard reaction time
The mathematics of infectious diseases
- SIAM Review
, 2000
"... Abstract. Many models for the spread of infectious diseases in populations have been analyzed mathematically and applied to specific diseases. Threshold theorems involving the basic reproduction number R0, the contact number σ, and the replacement number R are reviewed for the classic SIR epidemic a ..."
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Cited by 465 (4 self)
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Abstract. Many models for the spread of infectious diseases in populations have been analyzed mathematically and applied to specific diseases. Threshold theorems involving the basic reproduction number R0, the contact number σ, and the replacement number R are reviewed for the classic SIR epidemic
Understanding Productivity: Lessons from Longitudinal Microdata
, 2000
"... This paper reviews research that uses longitudinal microdata to document productivity movements and to examine factors behind productivity growth. The research explores the dispersion of productivity across firms and establishments, the persistence of productivity differentials, the consequences of ..."
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Cited by 382 (4 self)
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This paper reviews research that uses longitudinal microdata to document productivity movements and to examine factors behind productivity growth. The research explores the dispersion of productivity across firms and establishments, the persistence of productivity differentials, the consequences of entry and exit, and the contribution of resource reallocation across firms to aggregate productivity growth. The research also reveals important factors correlated with productivity growth, such as managerial ability, technology use, human capital, and regulation. The more advanced literature in the field has begun to address the more difficult questions of the causality between these factors and productivity growth.
What memory is for
- Behavioral and Brain Sciences
, 1997
"... What working memory is for Citation for published version: Logie, RH 1997, 'What working memory is for ' Behavioral and Brain Sciences, vol 20, no. 1, pp. 28. Link: Link to publication record in Edinburgh Research Explorer ..."
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Cited by 379 (5 self)
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What working memory is for Citation for published version: Logie, RH 1997, 'What working memory is for ' Behavioral and Brain Sciences, vol 20, no. 1, pp. 28. Link: Link to publication record in Edinburgh Research Explorer
Where do interorganizational networks come from?
, 1998
"... Organizations enter alliances with each other to access critical resources, but they rely on information from the network of prior alliances to determine with whom to cooperate. These new alliances modify the existing network, prompting an endogenous dynamic between organizational action and network ..."
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Cited by 377 (11 self)
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and network structure that drives the emergence of interorganizational networks. Testing these ideas on alliances formed in three industries over nine years, the authors show that the probability of a new alliance between specific organizations increases with their interdependence, but also with their prior
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