Seasonal and Diurnal Variations in Long‐Period Noise at SPREE Stations: The Influence of Soil Characteristics on Shallow Stations’ Performance
Bibliographic record
Abstract
The Superior Province Rifting Earthscope Experiment (SPREE) recorded \ncontinuous seismic data over the Midcontinent Rift from April 2011 through October \n2013. Analysis of power spectral density (PSD) estimates shows that horizontal noise \nlevels at periods >20 s vary seasonally and diurnally. During winter, horizontal noise \npower at many SPREE stations is within 5 dB of nearby Transportable Array (TA) \nstations. As the ground thaws, SPREE stations in fine-grained material such as silt or \nclay become noisier due to changes in the mechanical properties of the soil. During \nsummer, the daily mean PSD value of stations in fine-grained material is approximately \n10–20 dB higher than in the winter, and daytime noise levels are 20–30 dB \nhigher than nights. Stations in sandy material also show diurnal variations of \n20–30 dB during summer, but the daily mean PSD value varies no more than 5–10 dB \nduring the year. Most neighboring TA stations have relatively constant daily mean \nPSDs, and their horizontal components show summer diurnal variations of 10–15 dB. \nSome very quiet TA stations, such as SPMN, show a 5–10 dB increase in horizontal \nnoise power during winter. The timing and amplitude of horizontal noise power variations \nbetween 20 and 800 s correlate with variations in atmospheric pressure PSDs. \nWe propose that the grain size and pore water content of the material surrounding a \nshallow seismic station influences the local response to atmospheric pressure. Stations \nthat must be placed in soft sediments should be installed in sandy, well-drained \nmaterial to minimize long-period noise generated by atmospheric pressure variations.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".