Point estimates of Crustal thickness Using receiver Function Stacking
Bibliographic record
Abstract

 
 
 Introduction: Through receiver function analysis, this study inquires into some of the most basic properties of the crust below southern and central Quebec. Methods: This is accomplished, using receiver function technique, by stacking waveforms from 277 teleseismic events magnitude 6.0 and larger to find the delay in arrival time for several phases of the p-wave coda, relative to the initial p-wave arrival. This information is used to establish a linear relationship between thickness and p- to s-wave velocity ratio, each of which is stacked for a given station to identify a best-fit estimate for depth to the moho and Vp/Vs ratio. To determine their accuracy these results are compared with previous seismic studies, as well as synthetically generated receiver function p-wave arrivals based on simple 1d crustal models. Thickness calculations for the crust varied from 28 to 48 km; variation which was most likely the result of either complicated 3d structures or a shortage of available high-magnitude events for some stations. most of the results fell within appropriate windows outlined by studies like liTHoprobe. discussion: given that the 9 broadband stations used in this study compose an area from the superior province, grenville province and a selection of their subprovinces and intrusions, reliable evaluations of the crustal thicknesses below these seismic stations have broad relevance in understanding the crustal structure below Quebec.
 
 
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 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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".