Detecting anomalous turbidity patterns in nearshore waters of Québec based on CALIOP waveforms
Bibliographic record
Abstract
Coastal erosion is a major environmental issue affecting diverse infrastructures (e.g., buildings, roads, and ports) in Québec. In situ monitoring of coastal morphological changes and associated modifications on water turbidity is costly and face several challenges related to long-term marine measurements (e.g., biofouling). Here, a new technique based on spaceborne Lidar (Light detection and range) measurements is evaluated for estimating bi-weekly variations on suspended particulate matter off theQuébec coast. These preliminary results are part of FLASH (Fluvial bathymetry using spaceborne Laser in SHallow waters), an international project aiming to develop remote sensing tools for tracking unusual patterns of water turbidity linked to coastal desintegration (e.g., sediment plumes) in coastal environments of Canada and France. The experiments were performed in La Boule Bay east of Sept-Iles during April-July 2010 and involved comparisons between CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) measurements (L1_cal-v4 and 0.5 km CPRO products) and in-water turbidity measurements derived from an acoustic doppler current profiler (ADCP). La Boule Bay is an area of the northern shore of the Gulf of St. Lawrence that is undergoing presently a major coastal retreat after stability/advance during 70 years. Contrasting case studies based on high and low turbidity events showed a good correspondance between CALIOP volume backscattering at 532 nm (cross and co-polarized channels) and amplitude values of ADCP pings. Turbidity peaks usually coincided with neap tides, high winds, and larger wave heights.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".