Crustal Electrical Conductivity Structure of Yarlung Zangbo Jiang Suture in Southern Tibetan Plateau
Bibliographic record
Abstract
Abstract To study the structure in the shallow and deep crust along the east‐west and north‐south direction beneath the Yarlung Zangbo Jiang suture in the southern part of Tibetan plateau, three magnetotelluric profiles with super‐wide band of frequencies (Cona‐Maizhokunggar, Yadong‐Xuegula, Gyirong‐Coqên) across the Yarlung Zangbo Jiang suture were deployed. The result shows that large‐scale high resistive bodies exist near the Yarlung Zangbo Jiang suture surface, which extend to the maximum depth of more than 30km. They are the reflection of the Gangdise granite. There are small‐scale conductive bodies in the southern part of the Yarlung Zangbo Jiang suture, and large‐scale ones under the suture and in the northern part. Conductive bodies widely spread in the crust from south to north along the profiles. They are discontinuous with each other, and become larger in scale from south to north. They decline to the north, and are the steepest near the suture becoming deeper gradually from about 20km depth in the south part to about 70km depth in the middle of the suture. Under the Yarlung Zangbo Jiang suture, the conductive bodies becomes larger in scale, more conductive gradually from west to east. These important electrical characters are possibly caused by the India plate underthrusting to the north. The variation in characters of the large‐scale conductive bodies from west to east may be the proof that plate collision causes materials moving to the east.
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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 | 0.002 | 0.002 |
| 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".