Taking advantage of petrostructural heterogeneities in subduction-collisional orogens, and effect on the scale of analysis
Bibliographic record
Abstract
Since the beginning of the last century, tectonic history of polyphase metamorphic tectonites of orogenic basement complexes is often related to primary links with metasediments, of presumably known origin, and location of their original basins. However such history is worth to be compared with results of an alternative, independent investigation that pursues: i) an objective reconstruction of the evolutionary steps modifying the lithostratigraphic setting and of its deformation-metamorphism interactions during plate-scale events, and ii) a privileged reconstruction of the rock memory for the structural and metamorphic correlation of crystalline basement units. Interpretative merging of data gathered from these affine rock properties made interpretations of orogenic zones more actualistic and based on recognition of tectonic trajectories of units through evolving geodynamic contexts. In this account a refinement of the analytical approach to inferring deformation and metamorphic paths and constructing geological histories of basements in axial zones of orogenic belts is presented and examples are synthesized from the Western Alps and the Canadian Cordillera, based on detailed structural and lithostratigraphic mapping in harmony with macro- and micro- structural techniques of analysis, are reported from the two belts.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".