Independent component analysis of local‐scale temporal variability in sediment‐water interface temperature
Bibliographic record
Abstract
Abstract Temperature recorded at the sediment‐water interface has been identified as a valuable tracer for understanding groundwater‐surface water interactions. However, factors contributing to the variability in temperatures can be difficult to distinguish. In this study, the temporal variability in daily temperatures at the sediment‐water interface is evaluated for a 40 m reach of a coastal stream using Independent Component Analysis (ICA). ICA separation is used to identify three independent temperature components within the reach for each of four summer periods (2008–2011). Extracted temperature signals correlate with stream discharge, estimated streambed temperature, and groundwater level, but the strength of the correlations varies from summer to summer. Overall, variations in the temperature signals have clearer separation in summers with lower stream discharge and greater stream temperature ranges. Surface heating from solar radiation is the dominant factor influencing the sediment‐water interface temperature in most years, but there is evidence that thermal exchanges are taking place other than at the air‐water interface. These exchanges take place at the sediment‐water interface, and the correlation with groundwater levels indicates that these heat exchanges are associated with groundwater inflow. This study demonstrates that ICA can be used effectively to aid in identifying component signals in environmental applications of small spatial scale.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 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".