A simplified Red Bed Inclination Correction: Case Study from the Permian Esterel Group of France.
Bibliographic record
Abstract
Magnetic anisotropy-based inclinations corrections have been performed in the paleomagnetic laboratory at Lehigh University, on both hematite and magnetite-bearing sedimentary rocks. Results of these corrections indicate a latitudinal variation of inclination shallowing with the formations initially located at mid latitudes suffering from more shallowing than those initially closer to the equator, consistent with the tan (Im)= f * tan (If) relationship observed by King (1955) for inclination shallowing, where Im is the measured inclination and If is the field inclination during deposition. Shallowing of the \npaleomagnetic vectors can be expressed in terms of the flattening factor f, that relates tan (Im) to tan (If). Anisotropy- derived hematite f factors from the Maritime Provinces of Canada and Northwest China were combined with f factors derived from corrections that use models of geomagnetic field secular variation (the EI technique of Tauxe and Kent, 2004) on red bed Formations from North America, Greenland and Europe. The dataset was used to derive a probability density function for f. The mean f value will allow a simplified inclination correction for hematite-bearing red bed formations that are \nsuspected to be affected by inclination shallowing. This approach was tested by correcting the Permian Esterel Group red beds from France: using the distribution mean f factor of 0.64 (±0.11, ±1 standard deviation), the corrected red bed paleopole becomes statistically indistinguishable from the paleopole measured for the Esterel Group volcanic rocks that have not suffered from inclination shallowing. f data was also compiled for magnetite-bearing sedimentary rocks from the Perforada Formation and the Valle Group from Baja California, Mexico, the Pigeon Point Formation of Central California, the Ladd and the Point Loma Formations from Southern California, the Nanaimo Group of British Columbia and the Deer Lake Group of Newfoundland that have been corrected for inclination shallowing, yielding a most probable f factor of 0.67 (±0.06). Based on our results, the maximum amounts of shallowing that can be expected for sedimentary rocks is 12.4° for hematite-bearing rocks, and 11.8° for magnetite-bearing rocks. These values are statistically indistinguishable. Therefore, we combined the datasets and have obtained an f factor of 0.66 (±0.1) that can be used for either hematite or magnetite-bearing sedimentary rocks. A major implication of this result is that a rock's NRM, either acquired by chemical processes soon after deposition or by depositional processes that accurately record the ambient magnetic field, may be susceptible to similar amounts of inclination shallowing, most likely caused by burial compaction.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".