Seismic characterization for underground construction projects using microtremor survey method: A case study in Chengdu Line 18
Bibliographic record
Abstract
Microtremor Survey Method is utilized to map the near-surface velocity structure for a proposed subway construction project in Shenzhen, China. Three components broad-band seismometers are deployed in circular arrays on multiple survey points along the subway line. The recorded microtremor ‘noise’ is processed using SPAC method to obtain phase velocity dispersion curve for the fundamental mode of Rayleigh wave and subsequently inverted for S-wave velocities. HVSR is analyzed to probe possible anomalous geological structures potentially disruptive to the boring process. In this study, it is demonstrated that phase velocities for the frequency range from 8Hz to 40 Hz can provide reasonable solvability for structures down to 30 m and map the bedrock topography. Profiling the phase velocity dispersion curve and HVSR along the survey line allows the provision of a snapshot of the geological structure beneath. Presentation Date: Wednesday, October 17, 2018 Start Time: 1:50:00 PM Location: 204A (Anaheim Convention Center) Presentation Type: Oral
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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 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".