Water preparation methods of dissolved organic fraction determination for C-14 AMS measurements
Bibliographic record
Abstract
The determination of 14C in dissolved inorganic carbon (DIC) fraction has important task in nuclear environmental monitoring and water base protection. The aim of my research is to develop a preparation method for the 14C determination of dissolved organic carbon (DOC) and to develop sample preparation of total carbon containing both organic and inorganic fractions. In practice, the measurement of dissolved inorganic carbon (DIC) 14C is of essencial importance for example in environmental studies, as the amount of DIC is usually more than 100 times the amount of DOC and there is an easy, rapid preparation method. However, it is often difficult to interpret water dating and water residence time by measurement of dissolved inorganic fraction, because DIC dissolved in water can come from several sources: deep CO2 uptake and bedrock dissolution, not only from the surface biogenic environment at the time of seepage. Therefore, the measurement of dissolved organic carbon (DOC) component gets more importance around nuclear facilities because of its efficiency in detection of anthropogenic effect. To this aim, preparation methods have been developed that are suitable to determine the specific 14C activity concentration of the total dissolved carbon (TD14C) as well as of the dissolved organic form (non-purgeable organic fraction). The measurement of 14C in organic form is a difficult task, the amount of material is usually very small (only a few µg) and samples are difficult to handle furthermore the necessary sample volume usually is more than 500 mL. One of the solutions for DO14C sample preparation is an application of wet oxidation method. In this case the organic components are oxidized by acid and CO2 is extracted. This type of sample preparation technique is basically very sensitive about modern and fossil carbon contamination. However, the method has the additional disadvantage of high chemical demand (hence the contamination introduced) and a complicated and long sample preparation process. These disadvantages can be overcome by testing the total dissolved fraction 14C, which contains both fraction: inorganic and organic forms. Sample preparation can be performed in a significantly shorter time and at lower cost and can be used effectively alongside DI14C for the detection and monitoring of organic forms, for example in environmental monitoring of nuclear facilities. By determining DI14C and TD14C and carbon concentrations, DO14C can be estimated with a good approximation (±10% rel. error). ,,Prepared with the professional support of the Doctoral Student Scholarship Program of the Co-operative Doctoral Program of the Ministry of Innovation and Technology financed from the National Research, Development and Innovation Fund.” The research was supported by the European Union and the State of Hungary, co-financed by the European Regional Development Fund in the project of GINOP-2.3.4-15-2020-00007 “INTERACT”.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".