Shear Wave Splitting and Mantle Flow beneath Alaska Data Set
Bibliographic record
Abstract
Entire data set for the (under review) publication "Shear Wave Splitting in Alaska." McPherson_S1_Station_Info is a table that contains the following columns (with header row): Station Name, Network, Latitude (Deg), Longitude (Deg). This is a table of all the seismic stations in Alaska and western Canada that we downloaded data from. Only stations that were active from Jan 1, 2010, to Aug 18, 2017 are included. McPherson_S2_Event_Info is a table that contains the following columns (with header row): Julian Date, Origin Time, Latitude (Deg), Longitude (Deg), Depth (km), Magnitude (Mw). This is a table of all the seismic events that occurred between Jan 1, 2010, to Aug 18, 2017 within the distance range 80 to 140 degrees from a station, over moment magnitude 5. McPherson_S3_Results_Info is a table that contains the following columns (with header row): Station Name, Back Azimuth (Deg), Distance (Deg), Fast Direction (Deg), Lower Bound (Deg), Upper Bound (Deg), Time Difference (sec), Lower Bound (sec), Upper Bound (sec), Julian Date, Origin Time. This table contains all of the minimum energy method (Silver & Chan, 1991) results that are displayed in Figures 4, 6-12 of the paper under review. McPherson_S4_Nulls_Info is a table that contains the following columns (with header row): Station Name, Back Azimuth (Deg), Distance (Deg), Julian Date, Origin Time. This tables contains all the null results displayed in Figure 5 of the paper under review.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 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) | 0.034 | 0.020 |
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".