Active and Passive Seismic Imaging of the Central Abitibi Greenstone Belt, Larder Lake, Ontario
Bibliographic record
Abstract
Abstract Passive seismic methods are considered cost‐effective and environmentally friendly alternatives to active (reflection) seismic methods. We have acquired colocated active and passive seismic surveys over a metal‐endowed Archean granite‐greenstone terrane in the Larder Lake area to investigate the reliability of estimated elastic properties using passive seismic methods. The passive seismic data were processed using two different data processing approaches, ambient noise surface‐wave tomography (ANSWT) and receiver function analysis, to generate shear‐wave velocity and P to S wave ( P ‐ S ) convertibility profiles of the subsurface, respectively. The Cadillac‐Larder Lake Fault (CLLF) was imaged as a south‐dipping subvertical zone of weak reflectivity in the reflection seismic profile. To the north of the CLLF, a package of north‐dipping reflections in the upper crust (at depths of 5–10 km) resides on the boundary of high (on the top) and low (on the bottom) shear‐wave velocity zones estimated using the ANSWT method. This package of reflections is most likely caused by overlaying mafic volcanic and underlying felsic intrusive rocks. The P ‐ S convertibility profile imaged the Moho boundary at ∼40‐km depth as well as a south‐dipping feature that penetrates the mantle, which is interpreted to be either caused by the delamination of the lower crust or a possible deeper extension of the Porcupine‐Destor Fault. Overall, the reflectivity, shear‐wave velocity, and P ‐ S convertibility profiles exhibit a good correlation and provided a detailed image of the subsurface lithological structure to a depth of 10 km.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".