Empiricism and model building in stratigraphy: The historical roots of present-day practices
Bibliographic record
Abstract
The science of Stratigraphy has, since its inception in the late eighteenth century, been characterized by two contrasting research modes or "cognitive styles" (Rudwick 1982). Empirical (inductive) descriptive stratigraphy began with William Smith, led to the establishment of a data base of stratigraphic units (Murchison, Sedgwick, Lapworth), and formed the basis for modern work to establish and refine a detailed chronostratigraphic time scale (Van Hinte, Berggren). Other workers (Hutton, Lyell, Darwin, Chamberlin, Ulrich, Umbgrove, Sloss, Vail) have sought to identify underlying geological controls, and have built deductive models to explain earth processes, beginning with Hutton's uniformitarianism. Many such models sought evidence of regularity or cyclicity in earth processes ("the pulse of the earth"), including the modern "global-eustasy" model of Vail. There is an ever present danger that models can drive the analysis and presentation of data, particularly where stratigraphic models have been invoked to explain, clarify or codify the stratigraphic record. These problems are not new. Attempts to apply European chronostratigraphic units to North American stratigraphy in the early twentieth century were accompanied by expectations that unit boundaries would be marked by lithologic events, such as unconformities. These expectations were not supported, and this may have been the basis for North American attempts to establish alternative stratigraphies, including what became sequence stratigraphy. Ulrich (1911) thought that stratigraphic successions were created by "diastrophic cycles", and was concerned that regional correlations of these successions did not appear to be supported by the biostratigraphic evidence. Barrell (1917) was one of the first to understand the problems created by the lack of representation of long intervals of time in the geologic record, and developed ideas concerning the relationship between base level change and sedimentation that we now term �accommodation.†Modern work on the chronostratigraphic time scale is based on empirical principles, culminating in the definition of global section and boundary stratotypes for the major chronostratigraphic units. However, a controversy has recently arisen over the preference by some geologists to use distinctive marker events to define boundaries. In some cases, this involves introducing hypotheses about the global extent and geological superiority of such events, rather than relying on the accumulated historical record of biostratigraphic and other data.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".