Saint John Harbour Macroalgal & Phytoplankton Monitoring Project (2020-2023)
Bibliographic record
Abstract
This project provides a baseline survey of the macroalgae (seaweed) and phytoplankton of the Saint John Harbour and the microbiome of the nearby Musquash Estuary. Surveys were performed in Spring and Fall of 2020 and 2023 and encompassed 6 intertidal sites, 14 subtidal sites, 6 phytoplankton sites and 6 estuary sites. The provided data include: (1) quantitative intertidal counts of macroalgae based on morphological identification, (2) qualitative surveys of macroalgae present at each site based on molecular data (rbcL 3P), (3) eDNA of phytoplankton tows and (4) eDNA of estuarine mud scrapes. Quantitative macroalgal data were collected across a horizontal transect with 8 quadrats at each site in each of four sampling periods. Traditional molecular methods were used to generate the 3P end of the rbcL gene (for more details, see Saunders & Moore, 2013, https://doi.org/10.4490/algae.2013.28.1.031) and all eDNA data were generated by the Integrated Microbiome Resource at Dalhousie University. This project was funded by Fisheries and Oceans Canada's Coastal Environmental Baseline Program under the Oceans Protection Plan.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.010 |
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".