Bibliographic record
Abstract
16-station broadband seismographic network was deployed in northeastern China along the North Korea - China border during June 2004 and September 2010. The network had been deployed to study geophysical property in the region, particularly the Paekdusan (Changbei shan) volcano region. The stations consist of CMG-40T and CMG-3ESP broadband sensors with Orion and Taurus dataloggers from Nanometrics, Canada. Digital data were recorded continuously with a rate of 100 samples/s. The PI of the network was Dr. Kin-Yip Chun - formerly of University of Toronto, Canada and local staff at the Seismic Bureaus of Jilin and Lianing Provinces in China maintained the network. In a recent year, Kin-Yip Chun sent hard disk drives with raw data to Lamont-Doherty Earth Observatory of Columbia University for developing database suitable for archiving and further dissemination. Drs. Paul Richards, Won-Young Kim, and David Schaff at Lamont contributed to build the database.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.035 |
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".