Detectability of alkalinity plumes during the OAE field trial: A Bedford Basin case study
Bibliographic record
Abstract
In the Fall of 2023, in collaboration with Dalhousie University researchers, Planetary Technologies completed a first-of-a-kind series of alkalinity releases in the Bedford Basin/Halifax Harbour (Canada) using several alkalinity sources at varying dosing rates. These OAE trials aimed to test the detectability of alkalinity plumes resulting from the addition of varying amounts of alkalinization material and the different types of material - dissolved or particulate. Detectability of the released alkalinity was examined by observing the changes in the carbonate system of seawater measured in the water samples and by the sensor-equipped in situ platforms - fixed and mobile – before, during and after the trials. The collected data was used to test and validate the regional biogeochemical model (ROMS) available for the Bedford Basin, which largely informed the sampling design during the trial.We will present the challenges encountered, results and insights gained during the field trials in the Bedford Basin/Halifax Harbour in the Fall of 2023, particularly focusing on improvements to the observational component in 2024. We will discuss the utility of the moored and profiling assets, surface and underwater vehicles, and various water sampling methods in tracking and characterizing alkalinity plumes during the OAE trials
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".