Bibliographic record
Abstract
ABSTRACT Large-scale crustal lineaments are recognized as corridors (up to 30 km wide) of aligned geological, structural, geomorphological, or geophysical features that are distinct from regional geological trends such as outcrop traces. They are commonly difficult to observe on the ground, the scale of the features and their interrelationships being too large to map except at a regional scale. They are therefore most easily identified from satellite imagery and geophysical (gravity, magnetic) maps. Lineaments are believed to be the surface expressions of ancient, deep-crustal or trans-lithospheric structures, which periodically have been reactivated as planes of weakness during subsequent tectonic events. These planes of weakness, and in particular their intersections, may provide high-permeability channels for ascent of deeply derived magmas and fluids. Optimum conditions for magma penetration are provided when these structures are placed under tension or transtension. In regions of subduction-related magmatism, porphyry copper and related deposits may be generated along these lineaments because the structures serve to focus the ascent of relatively evolved magmas and fluid distillates from deep-crustal magma reservoirs. However, lineament intersections can only focus such activity where a magma supply exists, and when lithospheric stress conditions permit. A comprehensive understanding of regional tectono-magmatic history is therefore required to interpret lineament maps in terms of their prospectivity for mineral exploration.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.044 | 0.006 |
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".