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Sökning: WFRF:(Coles B)

  • Resultat 1-10 av 35
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  • Niemi, MEK, et al. (författare)
  • 2021
  • swepub:Mat__t
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  • Kanai, M, et al. (författare)
  • 2023
  • swepub:Mat__t
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3.
  • Buchanan, E. M., et al. (författare)
  • The Psychological Science Accelerator's COVID-19 rapid-response dataset
  • 2023
  • Ingår i: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 10:1
  • Tidskriftsartikel (refereegranskat)abstract
    • In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data.
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  • Hartley, Philippa, et al. (författare)
  • SKA Science Data Challenge 2: analysis and results
  • 2023
  • Ingår i: Monthly Notices of the Royal Astronomical Society. - 0035-8711 .- 1365-2966. ; 523:2, s. 1967-1993
  • Tidskriftsartikel (refereegranskat)abstract
    • The Square Kilometre Array Observatory (SKAO) will explore the radio sky to new depths in order to conduct transformational science. SKAO data products made available to astronomers will be correspondingly large and complex, requiring the application of advanced analysis techniques to extract key science findings. To this end, SKAO is conducting a series of Science Data Challenges, each designed to familiarize the scientific community with SKAO data and to drive the development of new analysis techniques. We present the results from Science Data Challenge 2 (SDC2), which invited participants to find and characterize 233 245 neutral hydrogen (H i) sources in a simulated data product representing a 2000 h SKA-Mid spectral line observation from redshifts 0.25-0.5. Through the generous support of eight international supercomputing facilities, participants were able to undertake the Challenge using dedicated computational resources. Alongside the main challenge, 'reproducibility awards' were made in recognition of those pipelines which demonstrated Open Science best practice. The Challenge saw over 100 participants develop a range of new and existing techniques, with results that highlight the strengths of multidisciplinary and collaborative effort. The winning strategy - which combined predictions from two independent machine learning techniques to yield a 20 per cent improvement in overall performance - underscores one of the main Challenge outcomes: that of method complementarity. It is likely that the combination of methods in a so-called ensemble approach will be key to exploiting very large astronomical data sets.
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  • Resultat 1-10 av 35

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