A remotely operated airboat for metal-free, ultraclean water sampling for trace elements in lentic waterbodies: from design and fabrication to operation in the field
Bibliographic record
Abstract
The mitigation of contamination during water sampling remains one of the primary challenges for trace elements research. In shallow water bodies, it is especially important to avoid disturbing the sediments to avoid the introduction of particles and colloids containing trace elements to the water column. Traditional sampling protocols can stir up sediments, and conventional equipment containing metal alloys presents additional sample contamination risks. Here we describe the design, construction, and testing of a metal-free unmanned, remotely operated airboat for sampling lentic freshwater habitats. The SWAMP airboat consists of two pontoons that support a water sampler containing four winches to lower and raise 60 mL bottles to sample from desired depths. The airboat is driven by two motorized propellers and is equipped with Cube Autopilot to stabilize the airboat during sample collection. • A 3D printer was used to construct plastic components for the airboat, composed of polyethylene terephthalate glycol (PETG), PolyMide™ CoPA nylon, high density polyethylene (HDPE), and polycarbonate (PC) carbon fiber. • Solenoids were programmed to remotely open and drop weights that open valves on the 60 mL sampling bottle to collect water at specified depths. • The SWAMP airboat was successfully field-tested at two locations in Alberta, Canada.
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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 | 0.001 | 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) | 0.000 | 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".