--- title: CODECHECK Register --- |Certificate |Report |Paper Title |Venue |Type |Check date | |:-------|:--------------------------------------------------|:----------------------------------|:---------------|:---|:--------------------------| |[2020-001](./certs/2020-001/)|[doi.org/10.5281/zenodo.3674056](http://doi.org/10.5281/zenodo.3674056)|[ShinyLearner: A containerized benchmarking tool for machine-learning classification of tabular data.](https://doi.org/10.1093/gigascience/giaa026) |[GigaScience](./venues/journals/gigascience)|[Journal](./venues/journals)|2019-02-14 | |[2020-002](./certs/2020-002/)|[doi.org/10.5281/zenodo.3750741](http://doi.org/10.5281/zenodo.3750741)|[The principal components of natural images](https://doi.org/10.1088/0954-898X_3_1_008) |[codecheck](./venues/communities/codecheck)|[Community](./venues/communities)|2020-04-13 | |[2020-003](./certs/2020-003/)|[doi.org/10.5281/zenodo.3741797](https://doi.org/10.5281/zenodo.3741797)|[Neural networks and physical systems with emergent collective computational abilities](https://doi.org/10.1073/pnas.79.8.2554) |[codecheck](./venues/communities/codecheck)|[Community](./venues/communities)|2020-04-06 | |[2020-004](./certs/2020-004/)|[doi.org/10.5281/zenodo.3827371](https://doi.org/10.5281/zenodo.3827371)|[Neuronlike adaptive elements that can solve difficult learning control problems](https://doi.org/10.1109/TSMC.1983.6313077) |[codecheck](./venues/communities/codecheck)|[Community](./venues/communities)|2020-05-14 | |[2020-005](./certs/2020-005/)|[doi.org/10.5281/zenodo.3959175](https://doi.org/10.5281/zenodo.3959175)|[[Re] Connectivity reflects coding: a model of voltage-based STDP with homeostasis ](https://doi.org/10.5281/zenodo.3538217) |[codecheck](./venues/communities/codecheck)|[Community](./venues/communities)|2020-07-23 | |[2020-006](./certs/2020-006/)|[doi.org/10.5281/zenodo.3948353](https://doi.org/10.5281/zenodo.3948353)|[[Re] A Generalized Linear Integrate-and-Fire Neural Model Produces Diverse Spiking Behaviours ](https://doi.org/10.5281/zenodo.1003214) |[codecheck](./venues/communities/codecheck)|[Community](./venues/communities)|2020-07-16 | |[2020-007](./certs/2020-007/)|[doi.org/10.53962/nsys-9a40](https://doi.org/10.53962/nsys-9a40)|[[Re] Spike Timing Dependent Plasticity Finds the Start of Repeating Patterns in Continuous Spike Trains ](https://doi.org/10.5281/zenodo.1327348) |[codecheck](./venues/communities/codecheck)|[Community](./venues/communities)|2025-05-19 | |[2020-008](./certs/2020-008/)|[doi.org/10.5281/zenodo.3746024](http://doi.org/10.5281/zenodo.3746024)|[The effect of non-pharmaceutical interventions on COVID-19 cases, deaths and demand for hospital services in the UK: a modelling study](https://cmmid.github.io/topics/covid19/control-measures/report/uk_scenario_modelling_preprint_2020_04_01.pdf)|[preprint](./venues/communities/preprint)|[Community](./venues/communities)|2020-04-09 | |[2020-009](./certs/2020-009/)|[doi.org/10.5281/zenodo.3767060](http://doi.org/10.5281/zenodo.3767060)|[Model of isolation, contact tracing, and physical distancing (Preprint)](https://cmmid.github.io/topics/covid19/reports/bbc_contact_tracing.pdf) |[preprint](./venues/communities/preprint)|[Community](./venues/communities)|2020-04-26 | |[2020-010](./certs/2020-010/)|[doi.org/10.5281/zenodo.3865491](https://doi.org/10.5281/zenodo.3865491)|[Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand. March 16, 2020. ](https://doi.org/10.25561/77482)|[preprint](./venues/communities/preprint)|[Community](./venues/communities)|2020-05-29 | |[2020-011](./certs/2020-011/)|[doi.org/10.5281/zenodo.3893138](https://doi.org/10.5281/zenodo.3893138)|[Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe ](http://doi.org/10.1038/s41586-020-2405-7) |[in press](./venues/communities/in_press)|[Community](./venues/communities)|2020-06-13 | |[2020-012](./certs/2020-012/)|[doi.org/10.5281/zenodo.3893617](https://doi.org/10.5281/zenodo.3893617)|[Report 23: State-level tracking of COVID-19 in the United States version 2 (28-05-2020) ](https://doi.org/10.25561/79231) |[preprint](./venues/communities/preprint)|[Community](./venues/communities)|2020-06-14 | |[2020-013](./certs/2020-013/)|[doi.org/10.5281/zenodo.3947959](https://doi.org/10.5281/zenodo.3947959)|[Rest-activity cycles and melatonin phase angle of circadian entrainment in people without cone-mediated vision ](https://doi.org/10.1101/2020.06.02.129502)|[preprint](./venues/communities/preprint)|[Community](./venues/communities)|2020-07-14 | |[2020-014](./certs/2020-014/)|[doi.org/10.5281/zenodo.3967326](https://doi.org/10.5281/zenodo.3967326)|[Patterned perturbation of inhibition can reveal the dynamical structure of neural processing ](https://doi.org/10.7554/eLife.52757) |[codecheck](./venues/communities/codecheck)|[Community](./venues/communities)|2020-07-28 | |[2020-015](./certs/2020-015/)|[doi.org/10.5281/zenodo.3978402](https://doi.org/10.5281/zenodo.3978402)|[A model for focal seizure onset, propagation, evolution, and progression ](https://doi.org/10.7554/eLife.50927) |[codecheck](./venues/communities/codecheck)|[Community](./venues/communities)|2020-08-04 | |[2020-016](./certs/2020-016/)|[doi.org/10.5281/zenodo.3981253](https://doi.org/10.5281/zenodo.3981253)|[Opening practice: supporting reproducibility and critical spatial data science ](https://doi.org/10.1007/s10109-020-00334-2) |[J Geogr Syst](./venues/journals/j_geogr_syst)|[Journal](./venues/journals)|2020-06-02 | |[2020-017](./certs/2020-017/)|[doi.org/10.5281/zenodo.4003848](https://doi.org/10.5281/zenodo.4003848)|[Progress in the R ecosystem for representing and handling spatial data](https://doi.org/10.1007/s10109-020-00336-0) |[J Geogr Syst](./venues/journals/j_geogr_syst)|[Journal](./venues/journals)|2020-08-27 | |[2020-018](./certs/2020-018/)|[doi.org/10.17605/OSF.IO/ZTC7M](https://doi.org/10.17605/OSF.IO/ZTC7M)|[Integrating cellular automata and discrete global grid systems: a case study into wildfire modelling](https://doi.org/10.5194/agile-giss-1-6-2020) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2020-07-13 | |[2020-019](./certs/2020-019/)|[doi.org/10.17605/OSF.IO/5SVMT](https://doi.org/10.17605/OSF.IO/5SVMT)|[What to do in the Meantime: A Service Coverage Analysis for Parked Autonomous Vehicles](https://doi.org/10.5194/agile-giss-1-7-2020) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2020-07-13 | |[2020-020](./certs/2020-020/)|[doi.org/10.17605/OSF.IO/7TWR2](https://doi.org/10.17605/OSF.IO/7TWR2)|[Window Operators for Processing Spatio-Temporal Data Streams on Unmanned Vehicles](https://doi.org/10.5194/agile-giss-1-21-2020) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2020-07-13 | |[2020-021](./certs/2020-021/)|[doi.org/10.17605/OSF.IO/SUWPJ](https://doi.org/10.17605/OSF.IO/SUWPJ)|[Comparing supervised learning algorithms for Spatial Nominal Entity recognition](https://doi.org/10.5194/agile-giss-1-15-2020) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2020-07-13 | |[2020-022](./certs/2020-022/)|[doi.org/10.17605/OSF.IO/7XRQG](https://doi.org/10.17605/OSF.IO/7XRQG)|[Extracting interrogative intents and concepts from geo-analytic questions.](https://doi.org/10.5194/agile-giss-1-23-2020) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2020-07-13 | |[2020-023](./certs/2020-023/)|[doi.org/10.17605/OSF.IO/XS5YR](https://doi.org/10.17605/OSF.IO/XS5YR)|[Tracking Hurricane Dorian in GDELT and Twitter](https://doi.org/10.5194/agile-giss-1-19-2020) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2020-07-13 | |[2020-024](./certs/2020-024/)|[doi.org/10.5281/zenodo.4964880](https://doi.org/10.5281/zenodo.4964880)|[Driftage: a multi-agent system framework for concept drift detection ](https://doi.org/10.1093/gigascience/giab030) |[GigaScience](./venues/journals/gigascience)|[Journal](./venues/journals)|2020-12-07 | |[2020-025](./certs/2020-025/)|[doi.org/10.5281/zenodo.4279275](https://doi.org/10.5281/zenodo.4279275)|[The application of Local Indicators for Categorical Data (LICD) to explore spatial dependence in archaeological spaces](https://doi.org/10.1016/j.jas.2020.105306)|[J Archaeol Sci](./venues/journals/j_archaeol_sci)|[Journal](./venues/journals)|2020-11-19 | |[2021-001](./certs/2021-001/)|[doi.org/10.5281/zenodo.4720843](https://doi.org/10.5281/zenodo.4720843)|[Causality indices for bivariate time series data: a comparative review of performance](https://arxiv.org/abs/2104.00718) |[preprint](./venues/communities/preprint)|[Community](./venues/communities)|2021-04-27 | |[2021-002](./certs/2021-002/)|[doi.org/10.17605/osf.io/rsf4m](https://doi.org/10.17605/osf.io/rsf4m)|[Building Change Detection of Airborne Laser Scanning and Dense Image Matching Point Clouds using Height and Class Information](https://doi.org/10.5194/agile-giss-2-10-2021)|[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2021-06-10 | |[2021-003](./certs/2021-003/)|[doi.org/10.17605/osf.io/dx92a](https://doi.org/10.17605/osf.io/dx92a)|[Investigating drivers’ geospatial abilities in unfamiliar environments](https://doi.org/10.5194/agile-giss-2-3-2021) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2021-06-10 | |[2021-004](./certs/2021-004/)|[doi.org/10.17605/osf.io/2sc7g](https://doi.org/10.17605/osf.io/2sc7g)|[Extraction of linear structures from digital terrain models using deep learning](https://doi.org/10.5194/agile-giss-2-11-2021) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2021-06-10 | |[2021-005](./certs/2021-005/)|[doi.org/10.17605/osf.io/7fqtm](https://doi.org/10.17605/osf.io/7fqtm)|[A Comparative Study of Typing and Speech For Map Metadata Creation](https://doi.org/10.5194/agile-giss-2-7-2021) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2021-06-10 | |[2021-006](./certs/2021-006/)|[doi.org/10.17605/OSF.IO/4CPM3](https://doi.org/10.17605/OSF.IO/4CPM3)|[A Socially Aware Huff Model for Destination Choice in Nature-based Tourism](https://doi.org/10.5194/agile-giss-2-14-2021) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2021-06-10 | |[2021-007](./certs/2021-007/)|[doi.org/10.17605/osf.io/anv9r](https://doi.org/10.17605/osf.io/anv9r)|[Automated Extraction of Labels from Large-Scale Historical Maps](https://doi.org/10.5194/agile-giss-2-12-2021) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2021-06-10 | |[2021-008](./certs/2021-008/)|[doi.org/10.17605/osf.io/g4dcq](https://doi.org/10.17605/osf.io/g4dcq)|[Flood Impact Assessment on Road Network and Healthcare Access at the example of Jakarta, Indonesia](https://doi.org/10.5194/agile-giss-2-4-2021) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2021-06-10 | |[2021-009](./certs/2021-009/)|[doi.org/10.17605/osf.io/rdnyu](https://doi.org/10.17605/osf.io/rdnyu)|[H-TFIDF: What makes areas specific over time in the massive flow of tweets related to the covid pandemic?](https://doi.org/10.5194/agile-giss-2-2-2021) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2021-06-10 | |[2021-010](./certs/2021-010/)|[doi.org/10.17605/osf.io/bdu28](https://doi.org/10.17605/osf.io/bdu28)|[An Approach to Assess the Effect of Currentness of Spatial Data on Routing Quality](https://doi.org/10.5194/agile-giss-2-13-2021) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2021-06-10 | |[2022-001](./certs/2022-001/)|[doi.org/10.5281/zenodo.6040066](https://doi.org/10.5281/zenodo.6040066)|[Geographically Weighted Regressions for prioritizing educational planning, policies, and interventions ](http://www.iiep.unesco.org/en/publication/geographically-weighted-regressions-prioritizing-educational-planning-policies-and)|[codecheck](./venues/communities/codecheck)|[Community](./venues/communities)|2022-01-19 | |[2022-002](./certs/2022-002/)|[doi.org/10.17605/osf.io/z7p8k](https://doi.org/10.17605/osf.io/z7p8k)|[Understanding the Imperfection of 3D point Cloud and Semantic Segmentation algorithms for 3D Models of Indoor Environment](https://doi.org/10.5194/agile-giss-3-2-2022)|[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2022-07-09 | |[2022-003](./certs/2022-003/)|[doi.org/10.17605/OSF.IO/JDTN3](https://doi.org/10.17605/OSF.IO/JDTN3)|[Optimizing Electric Vehicle Charging Schedules Based on Probabilistic Forecast of Individual Mobility](https://doi.org/10.5194/agile-giss-3-3-2022) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2022-07-09 | |[2022-004](./certs/2022-004/)|[doi.org/10.17605/osf.io/XPG6Y](https://doi.org/10.17605/osf.io/XPG6Y)|[What are intersections for pedestrian users?](https://doi.org/10.5194/agile-giss-3-4-2022) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2022-07-09 | |[2022-005](./certs/2022-005/)|[doi.org/10.17605/osf.io/cdfah](https://doi.org/10.17605/osf.io/cdfah)|[Spatial Disaggregation of Population Subgroups Leveraging Self-Trained Multi-Output Gradient Boosted Regression Trees](https://doi.org/10.5194/agile-giss-3-5-2022)|[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2022-07-09 | |[2022-006](./certs/2022-006/)|[doi.org/10.17605/osf.io/W7VPH](https://doi.org/10.17605/osf.io/W7VPH)|[Exploratory Analysis and Feature Selection for the Prediction of Nitrogen Dioxide](https://doi.org/10.5194/agile-giss-3-6-2022) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2022-07-09 | |[2022-007](./certs/2022-007/)|[doi.org/10.17605/OSF.IO/3DSMV](https://doi.org/10.17605/OSF.IO/3DSMV)|[Geoparsing: Solved or Biased? An Evaluation of Geographic Biases in Geoparsing](https://doi.org/10.5194/agile-giss-3-9-2022) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2022-07-09 | |[2022-008](./certs/2022-008/)|[doi.org/10.17605/OSF.IO/K78EB](https://doi.org/10.17605/OSF.IO/K78EB)|[Benchmarking Invasive Alien Species Image Recognition Models for a Citizen Science Based Spatial Distribution Monitoring](https://doi.org/10.5194/agile-giss-3-10-2022)|[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2022-07-09 | |[2022-009](./certs/2022-009/)|[doi.org/10.17605/osf.io/94vnx](https://doi.org/10.17605/osf.io/94vnx)|["Landmark Route": A Comparison to the Shortest Route](https://doi.org/10.5194/agile-giss-3-12-2022) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2022-07-09 | |[2022-010](./certs/2022-010/)|[doi.org/10.17605/osf.io/8b7mr](https://doi.org/10.17605/osf.io/8b7mr)|[Experimental evaluation of using BLE beacon for outdoor positioning in GPS-denied environment](https://doi.org/10.5194/agile-giss-3-13-2022) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2022-07-09 | |[2022-011](./certs/2022-011/)|[doi.org/10.17605/osf.io/kf8sr](https://doi.org/10.17605/osf.io/kf8sr)|[Understanding COVID-19 Effects on Mobility: A Community-Engaged Approach](https://doi.org/10.5194/agile-giss-3-14-2022) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2022-07-09 | |[2022-012](./certs/2022-012/)|[doi.org/10.17605/osf.io/r6psq](https://doi.org/10.17605/osf.io/r6psq)|[The Impact of Built Environment on Bike Commuting: Utilising Strava Bike Data and Geographically Weighted Models](https://doi.org/10.5194/agile-giss-3-15-2022)|[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2022-07-09 | |[2022-013](./certs/2022-013/)|[doi.org/10.17605/osf.io/3g9s8](https://doi.org/10.17605/osf.io/3g9s8)|[GeoXTag: Relative Spatial Information Extraction and Tagging of Unstructured Text](https://doi.org/10.5194/agile-giss-3-16-2022) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2022-07-09 | |[2022-014](./certs/2022-014/)|[doi.org/10.17605/osf.io/6s2gp](https://doi.org/10.17605/osf.io/6s2gp)|[A method to produce metadata describing and assessing the quality of spatial landmark datasets in mountain area](https://doi.org/10.5194/agile-giss-3-17-2022)|[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2022-07-09 | |[2022-015](./certs/2022-015/)|[doi.org/10.17605/osf.io/mvqcw](https://doi.org/10.17605/osf.io/mvqcw)|[Unlocking social network analysis methods for studying human mobility](https://doi.org/10.5194/agile-giss-3-19-2022) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2022-07-09 | |[2022-016](./certs/2022-016/)|[doi.org/10.17605/OSF.IO/DJFC2](https://doi.org/10.17605/OSF.IO/DJFC2)|[A machine learning based approach for predicting usage efficiency of shared e-scooters using vehicle availability data](https://doi.org/10.5194/agile-giss-3-20-2022)|[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2022-07-09 | |[2022-017](./certs/2022-017/)|[doi.org/10.17605/osf.io/wncsm](https://doi.org/10.17605/osf.io/wncsm)|[Traffic Regulation Recognition using Crowd-Sensed GPS and Map Data: a Hybrid Approach](https://doi.org/10.5194/agile-giss-3-22-2022) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2022-07-09 | |[2022-018](./certs/2022-018/)|[doi.org/10.5281/zenodo.7084333](https://doi.org/10.5281/zenodo.7084333)|[svaRetro and svaNUMT: Modular packages for annotation of retrotransposed transcripts and nuclear integration of mitochondrial DNA in genome sequencing data](https://doi.org/10.46471/gigabyte.70)|[GigaByte](./venues/journals/gigabyte)|[Journal](./venues/journals)|2022-09-27 | |[2023-001](./certs/2023-001/)|[doi.org/10.17605/osf.io/c7vx3](https://doi.org/10.17605/osf.io/c7vx3)|[Urban Sound Mapping for Wayfinding - A theoretical Approach and an empirical Study](https://doi.org/10.5194/agile-giss-4-9-2023) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2023-06-13 | |[2023-002](./certs/2023-002/)|[doi.org/10.17605/osf.io/rbgvk](https://doi.org/10.17605/osf.io/rbgvk)|[Evaluating and Comparing Airspace Structure Visualisation and Perception on Digital Aeronautical Chart](https://doi.org/10.5194/agile-giss-4-12-2023) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2023-06-13 | |[2023-003](./certs/2023-003/)|[doi.org/10.17605/osf.io/m5bhk](https://doi.org/10.17605/osf.io/m5bhk)|[Exploring MapSwipe as a Crowdsourcing Tool for (Rapid) Damage Assessment: The Case of the 2021 Haiti Earthquake](https://doi.org/10.5194/agile-giss-4-5-2023)|[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2023-06-13 | |[2023-004](./certs/2023-004/)|[doi.org/10.17605/osf.io/2em7v](https://doi.org/10.17605/osf.io/2em7v)|[Does spatial thinking ability relate to performance when using web-mapping services? A survey with digital natives](https://doi.org/10.5194/agile-giss-4-13-2023)|[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2023-06-13 | |[2023-005](./certs/2023-005/)|[doi.org/10.17605/osf.io/27wzp](https://doi.org/10.17605/osf.io/27wzp)|[Advancing Forest Monitoring and Assessment Through Immersive Virtual Reality](https://doi.org/10.5194/agile-giss-4-15-2023) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2023-06-13 | |[2023-006](./certs/2023-006/)|[doi.org/10.17605/OSF.IO/D2SHF](https://doi.org/10.17605/OSF.IO/D2SHF)|[Semantic complexity of geographic questions - A comparison in terms of conceptual transformations of answers](https://doi.org/10.5194/agile-giss-4-10-2023)|[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2023-06-13 | |[2023-007](./certs/2023-007/)|[doi.org/10.17605/osf.io/eu8kw](https://doi.org/10.17605/osf.io/eu8kw)|[Extreme heat alerts and impacts across Mozambique 2016 - 2022: gathering evidence from media articles](https://doi.org/10.5194/agile-giss-4-11-2023) |[AGILEGIS](./venues/conferences/agilegis)|[Conference](./venues/conferences)|2023-06-13 | |[2023-008](./certs/2023-008/)|[doi.org/10.17605/osf.io/aqgxr](https://doi.org/10.17605/osf.io/aqgxr)|[Is it safe to be attractive? 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