The Application of Automated SEM-Based Identification of Detrital and Diagenetic Mineral Phases in Offshore Cuttings from the Labrador Sea - Looking for the Source
Bibliographic record
Abstract
Abstract MLA-SEM analyses can quantitatively define the modal mineralogy of detrital components in a variety of sample material including offshore well cuttings such that the possible source(s) of the detrital material might be ascertained. The MLA data can be queried for combinations of detrital minerals that might reflect a specific source terrane (e.g., igneous suite, metamorphic complex, etc.). In some cases, minerals may be identified that might have a unique sediment source region. The MLA data can also be examined to evaluate whether trends of changing detrital mineral compositions through time (i.e., stratigraphically) can be documented that may reflect regional changes in the level of tectonism, potential unroofing a given sediment source area, and/or shifts between sediment source areas. The MLA analyses can be used to produce maps of radiometrically dateable mineral phases within a given sample, that might be used to derive radiometric dates.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.002 | 0.001 |
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".