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ZENODO
Software . 2023
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Software . 2023
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Software . 2023
Data sources: ZENODO
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NESOSIM with MCMC calibration

Authors: Alex Cabaj; Alek Petty;

NESOSIM with MCMC calibration

Abstract

NESOSIM version 1.1 with modifications to enable parameter calibration with a Markov Chain Monte Carlo method. Original model by Alek Petty; modifications made by Alex Cabaj. Refer to the main model record at https://zenodo.org/record/4448356 for additional information. A few additional files were added to enable model parameter calibration: mcmc_nesosim_buoy_dens_clim_io.py implements a 2-parameter MCMC calibration with observational constraints from Operation IceBridge snow depth, historical Soviet drifting station snow density, and additional snow depth measurements form CRREL-Dartmouth snow buoys. Outputs an HDF5 file containing accepted and rejected values of parameters, along with some statistics. (Will overwrite existing files unless file output paths are changed.) mcmc_nesosim_1par_ic_io.py implements the single-parameter version of this calibration, for reference. io_helpers.py is a script enabling the loading of multiple input files to memory to enable repeated runs of NESOSIM in the MCMC calibration without needing to re-read the same files from disk each time. NESOSIM.py and utils.py have been slightly modified to work with the MCMC calibration (mainly file I/O). Calibration input data is from Operation IceBridge, as aggregated by Petty et al (available at https://zenodo.org/record/6338558), CRREL-Dartmouth buoys (http://imb-crrel-dartmouth.org ) and Soviet drifting station data (Radionov et al, 1997).

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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