Control factors of pCO_2 and CO_2 degassing fluxes from the Yellow River in autumn
Bibliographic record
Abstract
The partial pressure of CO2(pCO2) in the water of the Yellow River was directly measured in November 2006, and the distribution and dynamics of pCO2 are discovered in the combination of the related parameters.The results indicate that the pCO2 in the surface water ranges between 80 and 166 Pa,with an average value of 110 Pa, and is lower than that in other important rivers in the world.Furthermore,the significant variations in the spatial pCO2 distribution, i.e,the pCO2 value in the middle part of the river is higher than upstream and downstream.Photosynthesis of phytoplankton has a slight effect on pCO2, even though Chla reaches the maximum 3.58 μg/L at Baotou station where the pCO2 value is still 91 Pa.Since the organic matter level in the Yellow River water is low and hard to degrade,the EpCO2/AOU value just varies from 0.14 to 0.20 in the mainstream and reservoir,lower than the theoretical value of 0.62,which suggests that the biological aerobic respiration effect has little contribution to pCO2.The content of TSS and DIC in the Yellow River water varies from 3.77 to 1308.33 mg/L and from 3.03 to 4.14 mmol/L,respectively,both of which are generally higher than other rivers in the world,and the maximum appears at Tongguan.Meanwhile the pCO2 has a positive relationships with TSS、PIC and DIC.So the main control factors of pCO2 are attributed to the carbonate system with high carbonate content induced by the strong mechanical erosion and chemical weathering in the Yellow River drainage area.Based on the model of Wanninkhof and the wind speed,the released CO2 from the Yellow River to atmosphere is estimated about 14.5×108 mol in autumn at the rate of 0.229 μmol/(m2·s),which is equal to the CO2 absorption of 8 250 km2 grass or 112 km2 forest.CO2 outgassing flux from the Yellow River is close to that of the Ottawa River and less than the Amazon River.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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 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".