Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Non-standard errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

The workshop "Physics with a multi-Megawatt (MMW) Proton Source"

The workshop ‘Physics with a multi-Megawatt (MMW) Proton Source' was held at CERN on 25-27 May 2004. It was organized by the ECFA/BENE working groups for future neutrino facilities in Europe and by the EURISOL nuclear physics community to explore the physics opportunities offered by a new high intensity proton accelerator. It confirmed the important synergies that exist between these communities. This document summarises the main design choices for the accelerators and experiments involved, the physics possibilities and the most critical R&D that will be necessary. A preliminary baseline road map is delineate

Benthic microalgae in coral reef sediments of the southern Great Barrier Reef, Australia

The abundance and productivity of benthic microalgae in coral reef sediments are poorly known compared with other, more conspicuous (e.g. coral zooxanthellae, macroalgae) primary producers of coral reef habitats. A survey of the distribution, biomass, and productivity of benthic microalgae on a platform reef flat and in a cross-shelf transect in the southern Great Barrier Reef indicated that benthic microalgae are ubiquitous, abundant (up to 995.0 mg chlorophyll (chl) a m(-2)), and productive (up to 110 mg O-2 m(-2) h(-1)) components of the reef ecosystem. Concentrations of benthic microalgae, expressed as chlorophyll a per surface area, were approximately 100-fold greater than the integrated water column concentrations of microalgae throughout the region. Benthic microalgal biomass was greater on the shallow water platform reef than in the deeper waters of the cross-shelf transect. In both areas the benthic microalgal communities had a similar composition, dominated by pennate diatoms, dinoflagellates, and cyanobacteria. Benthic microalgal populations were potentially nutrient-limited, based on responses to nitrogen and phosphorus enrichments in short-term (7-day) microcosm experiments. Benthic microalgal productivity, measured by O-2 evolution, indicated productive communities responsive to light and nutrient availability. The benthic microalgal concentrations observed (92-995 mg chl a m(-2)) were high relative to other reports, particularly compared with temperate regions. This abundance of productive plants in both reef and shelf sediments in the southern Great Barrier Reef suggests that benthic microalgae are key components of coral reef ecosystems