Faulting within the San Juan–southern Gulf Islands Archipelagos, upper plate deformation of the Cascadia subduction complex
Bibliographic record
Abstract
Abstract The San Juan–southern Gulf Islands Archipelago of Washington State, USA and western Canada is located on the upper plate of the Cascadia subduction zone, in the forearc between the trench and volcanic arc. Onland and island investigations show many faults within the region that primarily represent old, inactive faults associated with transport, subduction and accretion of tectonostratigraphic terranes. However, until recently little geologic investigation and mapping have been done in the offshore. From these narrow straits, channels and sounds we have collected and interpreted high-resolution multibeam echosounder bathymetric data, 3.5 kHz sub-bottom and Huntec seismic-reflection profiles, and piston-cores to identify and date recently active faults. Previous studies by us focused on the earlier recognized active Devils Mountain fault zone that bounds the southern part of the Archipelago and the recently reported newly mapped active Skipjack Island fault zone that bounds the northern part. These transcurrent fault zones appear to be deforming and rotating the Archipelago. We concentrate on the unique deformation occurring within the seaways to determine the relationship and styles of faulting associated with these active bounding fault zones and relate the fault geometry and kinematics to one other subduction complex, the New Hebrides island arc of Vanuatu.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".