COUPLING LITHIC SOURCING WITH LEAST COST PATH ANALYSIS TO MODEL PALEOINDIAN PATHWAYS IN NORTHEASTERN NORTH AMERICA
Bibliographic record
Abstract
Projections of Paleoindian range mobility in the late Pleistocene are typically inferred from straight-line distances between toolstone sources and sites where artifacts of these raw materials have been found. Often, however, these sourcing assessments are not based on geologic analysis, raising the issue of correct source ascription. If sites of similar age can be linked to a toolstone source through geologic study, and direct procurement of toolstone can be inferred, geographic information systems (GIS) modeling of travel routes between the source and those sites can reveal route segments of annual rounds and aspects of landscape use. In the Hudson Valley of eastern New York, Paleoindian peoples exploited Normanskill chert outcrops for toolstone during the late Pleistocene. Here, we combine X-ray fluorescence sourcing results that link Normanskill chert artifacts at Paleoindian sites to the West Athens Hill source outcrop in the Hudson Valley with GIS least cost path analysis to model seasonal pathways of late Pleistocene peoples in northeastern North America.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| 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".