A dataset of individual wet weights of benthic macroinvertebrates
Bibliographic record
Abstract
Abstract Biomass estimates are crucial for modeling and understanding energy flow through ecosystems. Many modeling frameworks rely on published body weights of organisms to convert density estimates to biomass. However, published body weight data are limited to few taxa in a limited number of systems. Here we present mean individual weights for common benthic macroinvertebrates of the Laurentian Great Lakes from over 2000 benthic samples and 8 yr of data collection. We also compiled wet to dry weight conversions to facilitate data reuse for researchers interested in dry weight. We compared our benthic invertebrate weights to other lakes, demonstrating when weight measurements may be applied outside the Great Lakes. Sensitivity analyses supported the robustness of our calculations. Our dataset is applicable to food web energy flow models, calculation of secondary production, interpretation of trophic markers, and for understanding how biomass distribution varies by benthic invertebrate species in the Great Lakes.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.000 |
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".