Magnetic resonance relaxation measurements using open-geometry sensors to assess the clog state of constructed wetlands
Bibliographic record
Abstract
Monitoring the T1 relaxation of wetland clog matter has previously been identified as a gauge of its clogged state [1]. Magnetic resonance (MR) sensors explored in other work have typically been of a bore-whole configuration, which may not be ideal in a wetland environment where the sensitive volume of the sensor may become physically clogged and therefore inoperable. This work investigates two open-geometry sensor designs and a short study is presented to determine the suitability of the sensors for monitoring the clog state of wetlands. It was shown that a bar magnet geometry has a higher stray field than that of the four magnet surface sensor also presented, leading to a prohibitively short T2 eff. This means that the T1 values collected are notably shorter and not useful for distinguishing between clog state for the single magnet sensor. By contrast the four magnet surface sensor has a longer T2 eff, making it more suitable for T1 measurements; where T1= 915 ± 212 ms for a very thinly clogged sample, and T1= 127 ± 27 ms for a heavily clogged sample. This offers a clearly resolvable difference in the T1 values allowing the clogging state to be easily determined and making this sensor the desirable choice for long-term embedding.
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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 | 0.000 | 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".