Glimpsing the 2020 spring bloom in the Strait of Georgia (Canada) with autonomous ferry-based sensors
Bibliographic record
Abstract
Spatiotemporal observations are data rich and offer insights into links between ecological patterns and underlying processes. We present fine-scale autonomous observations from repeated ferry transects in the Strait of Georgia (British Columbia, Canada) during the 2020 spring bloom period using a FerryBox system (temperature, salinity, chlorophyll a fluorescence) and a digital inline holographic microscope. Despite instrument cleaning interruptions related to COVID-19 restrictions, 3 periods from late winter (February) to springtime (March and April) contained 14 days of high-quality holograms (>70000) capturing >10500 identifiable micro- to mesoplankton using automatic object detection. The ferry set-up provided automatic data storage through Ocean Networks Canada, which also automatized data flagging and guaranteed remote access. The highest-quality holograms repeatedly covered the central and eastern Strait and showed aspects of bloom succession. Fast-growing diatoms ( Skeletonema sp.) emerged first, followed by a diverse assemblage including Chaetoceros spp., Ditylum spp., and Eucampia spp., and by April, larger centric cells prevailed. The combined approach captured local suppression of chlorophyll a fluorescence and diatom concentrations in Fraser River plume waters during the freshet, suggesting fine-scale spatial patterns in seasonal planktonic community composition. This work is among the first of its kind to autonomously generate in situ imaging and physicochemical data with spatiotemporal resolution.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".