Analyse chimique des inclusions fluides par ablation laser couplée à l’ICP-MS et applications géochimiques
Bibliographic record
Abstract
The study of paleofluids by using fluid inclusions analysis is an important challenge in geochemistry. The LA-ICPMS technique allows enlarging the field of possibilities by determining the cationic content in fluid inclusions. Three aims, with LA-ICPMS as the thesis centre, are developed here: (i) the calibration of LA-ICPMS associated with a work on chimiometry give the possibility of this analytical technique and experimental protocol adapted; (ii) The development of a calculation method based on Pitzer’s themodynamic model. The quantification of cationic content (trace and major elements) is improved. In parallel, a software is developed to facilitate the processing of raw signal, (iii) the study of different targets is made. The Cl/Br concentration ratios are used to get information of the fluids origin. Then, a analysis on four different natural targets linked with silver deposits is realized. The last point is the feasabilty of the determination of rare earth element in fluid inclusion of Mac Arthur River (Uranium deposit, Canada)
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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; both teacher heads agree on what is shown here.
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".