Diet Data from Fecal DNA Metabarcoding and Video Camera Collars from the Porcupine Caribou Herd, Alaska and Yukon
Bibliographic record
Abstract
These diet data were collected from the Porcupine caribou herd in northern Alaska and Yukon in summer 2021 during 4 periods: calving (occasion 1), post-calving (occasion 2), mosquito harassment (occasion 3), and mid-summer (occasion 4). Diet data was determined by two distinct techniques: DNA metabarcoding data from fecal pellets and video data from camera collars deployed on adult females. We provide five tables: (1) the raw number of reads/exact sequence variant (ESV) from the metabarcoding laboratory, (2,3) the relative read abundance from sequences with >90% DNA match to known plant and fungi taxa, (4) the raw forage data detected in 9-second videos, and (5) summarized video forage 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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; both teacher heads agree on what is shown here.
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".