Cladophora biomass and supporting data collected in the Great Lakes, 2021
Bibliographic record
Abstract
This dataset records Cladophora and associated benthic algae, collectively Cladophora community or submerged aquatic vegetation (SAV), biomass collected during the growing season of 2021 at stations located along the U.S. shoreline of Lakes Michigan, Huron, Erie, and Ontario. It also records a variety of supporting data collected at Cladophora measurement stations. These supporting data include: - seasonal time series of light, currents, wave action, temperature, specific conductivity, turbidity, pH, phycocyanin, chlorophyll, and dissolved oxygen from moored sensors at a subset of stations; - measurements of Secchi disk depth and water chemistry; - water column profiles of PAR, temperature, specific conductivity, turbidity, pH, phycocyanin, chlorophyll, and dissolved oxygen; - diver observations of SAV, dreissenid mussels, round goby abundance, and substrate properties; - measurements of dreissenid mussel abundance and size class distribution coincident with SAV biomass; - nutrient content of SAV, dreissenid mussels, and sediments; - and information about sampling locations and operations. Similar data were collected at several of the same transects within four Great Lakes in 2018, 2019, and 2020 are available at (2018) https://doi.org/10.5066/P9E570JS, (2019) https://doi.org/10.5066/P99O4QXB, and (2020) https://doi.org/10.5066/P9O9FSTT.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.006 |
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 source (direct Gemma or distilled Codex), 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".