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The Source-Scanning Algorithm: mapping the distribution of seismic sources in time and space

2004· article· en· 447 citations· W2137972163 on OpenAlex· 10.1111/j.1365-246x.2004.02276.x

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.

Full frame distilled prediction

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.

Candidate categories
none
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: ObservationalConsensus signal: none
Genre
Candidate signal: EmpiricalConsensus signal: Empirical
Teacher disagreement score
0.739
Threshold uncertainty score
0.222
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.011
GPT teacher head0.206
Teacher spread
0.196 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

We introduce a new method, which we call the Source-Scanning Algorithm (SSA), for imaging the distribution of seismic sources in both time and space. Using trial locations and origin times, the method calculates the ‘brightness’ function by summing the absolute amplitudes observed at all stations at their respective predicted arrival times. The spatial and temporal distribution of sources is then identified by a systematic search throughout the model space and time for the maximum brightness. The greatest advantages of this method are that: (1) it exploits waveform information (both arrival times and relative amplitudes) without the need to calculate high-frequency synthetic seismograms; and (2) it requires neither pre-assembled phase-picking data nor any a priori assumptions about the source geometry. A series of tests using synthetic data have shown that this method is robust and can faithfully recover the input source configuration to within 1 grid interval. Finally, we demonstrate the value of the algorithm by locating a typical tremor event with emergent waveforms that occurred during the recent episodic tremor and slip (ETS) sequence in the northern Cascadia subduction zone.

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.

The record

Venue
Geophysical Journal International
Topic
earthquake and tectonic studies
Field
Earth and Planetary Sciences
Canadian institutions
Geological Survey of Canada
Funders
not available
Keywords
SeismogramWaveformAlgorithmAmplitudeBrightnessA priori and a posterioriGeologyEpisodic tremor and slipComputer scienceSubductionSeismologyOpticsTelecommunicationsPhysics
Has abstract in OpenAlex
yes