Bibliographic record
Abstract
Abstract. Extreme climates affect the seasonal and interannual patterns of carbon (C) distribution due to the regimes of river inflow and thermal stratification within lentic ecosystems. Typhoons rapidly load substantial amounts of terrestrial C into subtropical small lakes, renewing and mixing the water column. We developed conceptual dissolved C models and hypothesized that allochthonous C loading and river inflow intrusion may affect the dissolved inorganic C (DIC) and dissolved organic C (DOC) distributions in a small subtropical lake under these extreme climates. A two-layer conceptual C models was developed to explore how the DIC and DOC fluxes respond to typhoon disturbances on seasonal and interannual time scales in a small subtropical lake (i.e., YuanâYang Lake) while simultaneously considering autochthonous processes such as algal photosynthesis, remineralization, and vertical transportation. Monthly field samplings were conducted to measure DIC, DOC, and chlorophyll a concentrations to compare the temporal patterns of fluxes between typhoon years (2015–2016) and non-typhoon years (2017–2018). The results demonstrated that net ecosystem production was 3.14 times higher in the typhoon years than in the non-typhoon years in YuanâYang Lake. The results suggested that the load of allochthonous C was the most crucial factor affecting the temporal variation of C fluxes in the typhoon years; on the other hand, the transportation rate shaped the seasonal C in the non-typhoon years due to thermal stratification within this small subtropical lake.
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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 | 0.002 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.021 | 0.020 |
| Insufficient payload (model declined to judge) | 0.156 | 0.121 |
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".