Bibliographic record
Abstract
One of the most exciting advances in Earth science in the last several decades has been our increased understanding of the structure and composition of the mantle. Seismic tomography and isotope geochemistry have been major players in those advances. The isotopic studies used basalts from ocean basins to minimize the problems of possible crustal contamination. Data from mid‐ocean ridge basalts (MORBs) and oceanic island basalts (OIBs) revealed a relatively detailed picture of the isotope geochemistry of the sub‐oceanic mantle [e.g. Hofmann, 1997] that led to the recognition of four principal magma components that define end‐member compositions. These are DMM, HIMU, EMI, and EM2 (see Table 1 for further details). All of these components except DMM have been attributed to subduction of different materials, such as oceanic and continental crust and lithosphere, down into the mantle. Several studies have indicated that the mantle is isotopically heterogeneous with heterogeneities that were probably established at least several billions of years ago.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.005 | 0.024 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.012 | 0.016 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".