Geometric Morphometric Analyses Support Incorporating the Goshen Point Type into Plainview
Bibliographic record
Abstract
Recent work has demonstrated that Goshen points overlap in time with another group of unfluted lanceolate points from the Plains, Plainview points. This has raised the question of whether the two types should be kept separate or consolidated into a single type. We sought to resolve this issue by applying geometric morphometric methods to a sample of points from well-documented Goshen and Plainview assemblages. We found that their shapes were statistically indistinguishable, which indicates that Goshen and Plainview points should be assigned to the same type. Because Plainview points were recognized before Goshen points, it is the latter type name that should be dropped. Sinking Goshen into Plainview allows us to move beyond taxonomic issues and toward understanding both the spatiotemporal variation that exists among Plainview assemblages and what it can tell us about the adaptations and social dynamics of Plainview groups.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.007 |
| 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) | 0.002 | 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 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".