Linear Programming Analysis and Diet Breadth Modeling at Bridge River, British Columbia
Bibliographic record
Abstract
Studies in diet breadth modeling and patch choice have been and continue to be a hot topic of interest among practitioners of human behavioral ecology and the set of data available at Bridge River can certainly add to these debates and discussions that have been dominating anthropology in the past few decades. The faunal assemblage of Housepit 54’s 17 anthropogenic floors have provided researchers with a plethora of data that clearly indicates periods of resource depletion and partial to full site abandonment. Using Linear Programming and Diet Breadth Modelling I analyze the most represented species in the record and establish an optimal projection for how best to utilize time fishing, hunting and gathering. While optimality is established on the basis of nutrition and time spent processing, correlation coefficients are also used to compare frequencies of salmon versus trout, deer, and other less desirable land vertebrates by floor layer. Establishing how the prehistoric peoples of Bridge River dealt with depletion of their most valued food resource of salmon could prove useful not just in increasing our knowledge of the events that transpired at Bridge River during this time but can also serve as a reference for how best to optimize dwindling resources in the 21st century.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".