Bibliographic record
Abstract
In the spirit of making data from the Radio Receiver Instrument (RRI) onboard Swarm-E (formally known as e-POP) more accessible to the ham radio community via the Ham Radio Science Citizen Investigation (HamSCI), we have converted RRI's data into a ".raw" format so that it can be ingested into open source software such as Gqrx or GNU Radio. We have done this for all RRI data related to the 2015, 2017, and 2018 ARRL Field Days. We encourage everyone to help us identify hams in RRI's signal. You can use the Gqrx tool discussed here, or you can use your own technique. If you decode a ham's call sign, if you would like to share your technique, or if you have any comments or suggestion contact us and let us know! Data Rules of the Road Please acknowledge the HamSCI project and Gareth Perry when using data from this archive in presentations and publications. Swarm-E RRI Swarm-E RRI is a digital radio receiver with 4 3-m monopole antennas. In most cases, the monopoles are electronically configured into a crossed-diople configuration. In this configuration, RRI records I/Q samples for the two dipoles. RRI has a sampling rate of 62500.33933 Hz, and a ~40 kHz bandpass, and can be tuned to anywhere between 10 Hz and 18 MHz. More information on Swarm-E RRI can be found in the Swarm-E RRI instrument paper or Gareth Perry's recent Radio Science article. Data Format Each data file contains raw 32 bit complex I/Q samples for a given RRI dipole at a given frequency. The samples are interleaved, e.g., IQIQIQIQ... The data files do not contain any metadata. Any information regarding the time, frequency, and corresponding RRI dipole is in the file name. Filename Format The filename format gives information about the time and data of the recording, the tuned frequency, and which of RRI's dipoles the recording corresponds too. For example, gqrx_20150628_011614_3525000_62500_RRI_Dipole1 contains data recorded on Dipole 1, starting at 01:16:14 UT on June 28, 2015, at 3525000 Hz (3.525 MHz), at a sampling rate of 62500 Hz (RRI's 62500.33933 Hz sampling rate). Gqrx We have opted to convert the data into the .raw format so that it can be ingested into Gqrx. There are other ways of analyzing RRI's data; this is just one way which we felt was as easy first step. We are open to posting about other techniques on the HamSCI site as well. To help get started with Gqrx, we have developed a How to play an RRI raw IQ file on Gqrx page.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.103 | 0.096 |
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".