Jericho open resistive data logger: An open-source modular weather station and monitoring system for long-term solar photovoltaic outdoor experimentation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Environmental and energy production monitoring systems not only provide data acquisition (DAQ) but now supervisory control and data acquisition (SCADA) for both meteorological and solar photovoltaic (PV) research. DIY systems are often not robust enough for research and proprietary systems are often economically prohibitive. The Jericho Open Resistive Data Logger (RDL) platform bridges this gap between low-cost DIY devices and high-cost proprietary DAQs. It integrates a custom RDL, Arduino Nano, modular I 2 C expansion, and a Raspberry Pi for edge processing into a robust, open-source platform. Supporting multiple sensor protocols (analog, digital, resistive, I 2 C, SDI-12, and USB) and long-distance wired transmission, the system enables reproducible, research-grade data collection at less than half of the cost of proprietary stations. Statistical comparison of irradiance, relative humidity and temperature and wind speed were bench marked against a proprietary system and found to be well within acceptable differences for validation although wind speed was found to have the highest deviation. Two independent open-source units confirm excellent inter-device repeatability across all measured variables. By combining environmental and PV monitoring within a unified platform, Jericho Open RDL provides an accessible and adaptable solution for distributed renewable energy and environmental research.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it