Bibliographic record
Abstract
Abstract Continental rift basins have long been of interest to sedimen-tologists. Of all the terrestrial depositional settings, rift basins typically provide the greatest accommodation space, and consequently have some of the longest records of continental sedimentation. These records are a product of a complex interplay between several factors. These include geological structure and tectonic activity, volcanism, climate and its temporal variability, hydrology, hydrogeology, biology, and time (Fig. 1). The lithological records in rifts, which are naturally dominated by fluvial and lacustrine deposits, have become increasingly prominent in recent years because of their potential for studying long-term climatic changes and for testing hypotheses of orbital forcing (e.g., Olsen, 1986; Johnson and Odada, 1996). More recently, the continuing quest for the paleontological and cultural records of human origins that are entombed in the sedimentary rocks of the East African rift has raised further questions on the tempo of climatic change, changing paleolandscapes, and the environmental stresses that might have affected human evolution (Vrba et al., 1995; Andrews and Banham, 1999). Rapid burial of thick sedimentary fills, high geothermal gradients, and consequent early maturation of lacustrine organic matter, much of which is sapropelic, have made rift basins attractive targets for petroleum exploration (e.g., Robbins, 1983; Katz, 1990; Lambiase, 1990, 1995). Indeed, most of our understanding of rift-basin geometry has resulted from seismic profiling sponsored by oil companies (Scholz et al., 1990; 1996;
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.037 | 0.017 |
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".