11 May 2024 Superstorm Ionospheric Observations in the Continental US
Bibliographic record
Abstract
May11_150km.mat: MATLAB save file - Ionospheric total electron content data from worldwide GNSS receivers, processed by MIT Haystack Observatory through the Millstone Hill Geospace Facility. Data is line of sight and conversion assumes a non-standard 150 km ionospheric pierce point. Direct permanent link: Anthea Coster, MIT/Haystack Observatory. (2024) Data from the CEDAR Madrigal database. Available from https://w3id.org/cedar?experiment_list=experiments4/2024/gps/11may24&file_list=los_20240511.001.h5 GPS TEC data products and access through the Madrigal distributed data system are provided to the community by the Massachusetts Institute of Technology under support from US National Science Foundation grant AGS-1952737. Data for the TEC processing is provided from the following organizations: UNAVCO, Scripps Orbit and Permanent Array Center, Institut Geographique National, France, International GNSS Service, The Crustal Dynamics Data Information System (CDDIS), National Geodetic Survey, Instituto Brasileiro de Geografia e Estatística, RAMSAC CORS of Instituto Geográfico Nacional de la República Argentina, Arecibo Observatory, Low-Latitude IonosphericSensor Network (LISN), Canadian High Arctic Ionospheric Network, Institute of Geology and Geophysics, Chinese Academy of Sciences, China Meteorology Administration, Centro di Ricerche Sismologiche, Système d'Observation du Niveau des Eaux Littorales (SONEL), RENAG: REseau NAtional GNSS permanent - https://doi.org/10.15778/resif.rg, GeoNet - the official source of geological hazard information for New Zealand, Finnish Meteorological Institute, SWEPOS - Sweden, Hartebeesthoek Radio Astronomy Observatory, TrigNet Web Application, South Africa, Australian Space Weather Services, RETE INTEGRATA NAZIONALE GPS, Estonian Land Board, TU Delft, Western Canada Deformation Array, EUREF Permanent GNSS Network, GeoDAF: Geodetic Data Archiving Facility, African Geodetic Reference Frame (AFREF), Kartverket - Norwegian Mapping Authority, Geoscience Australia, IGS Data Center of Wuhan University, Pacific Northwest Geodetic Array, Nevada Geodetic Laboratory, Earth Observatory of Singapore, National Time and Frequency Standard Laboratory - Taiwan, and Korea Astronomy and Space Science Institute. teczero.mat: MATLAB save file - 5-minute averaged background median TEC map, derived from May11_150km.mat file. TECmaps0.m: MATLAB script - plotting script, employing teczero.mat, and used for Figure 3 and Figure 4B of manuscript. gps_map.mat: MATLAB save file - source data for Figure 4A of manuscript: median vertical TEC map over 2-minute interval 0207-0208 UTC on 2024-05-11. Fig4a_map.m: MATLAB script - plotting script, employing gps_map.mat, and used for FIgure 4A of manuscript. cntr.m: MATLAB script - coastline plotting function. burst.m: MATLAB script - plots individual LOS TEC data showing TEC bursts. Saves to "bursts.mat". Inputs "May11_150km.mat". bursts.mat: MATLAB save file - individual TEC burst results. 1 Missouri_Skies_-_All-Sky_Fisheye_Missouri_Skies_Fishey_2030UT_2127UT.mp4: MP4 image file. Fisheye lens image of aurora from Missouri during 2024-05-11 storm. Used in Figure 2 of manuscript. {amt,att,bmt,bot,het,hmt,nmt,omt,pat,sum,vmt}240511.g.001.hdf5 - MagStar magnetometer measurements in HDF5 self-documenting file format, used for magnetometer figures in manuscript. Downloaded from the Madrigal database system. Direct permanent link: Jenn Gannon, Paul E. Meade, Eframir Franco-Diaz, Computational Physics. (2024) Data from the CEDAR Madrigal database. Available from https://w3id.org/cedar?experiment_list=experiments/2024/het/11may24&file_list=het240511g.001.hdf5. (Replace "het" with appropriate 3-letter site name from above list).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.141 | 0.106 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".