L’influence de la granulométrie sur la mesure des carbonates par la méthode du Chittick
Bibliographic record
Abstract
Des études récentes sur la composition minéralogique de sédiments argileux de la vallée du Saint-Laurent incluaient l'utilisation de la méthode du Chittick pour la détermination des quantités respectives de calcite et de dolomite. Lors d'essais préliminaires de calibration, il est apparu que la granulométrie de ces phases minérales pouvait grandement influencer les résultats. Afin de quantifier ce problème, plusieurs échantillons de granulométrie variée et contrôlée ont été dosés. La méthode du Chittick s'avéra alors très bonne pour le dosage de la teneur totale en carbonates mais faible pour le dosage individualisé de la calcite et de la dolomite en raison de sa forte sensibilité à la granulométrie des carbonates et à leur surface spécifique. Ainsi, les échantillons de dolomite pure ont montré une teneur apparente en calcite de 15 à 66%, selon leur granulométrie. L'addition d'une analyse chimique de la solution résiduelle obtenue au terme de l'essai permet toutefois d'obtenir les concentrations réelles de ces deux carbonates.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".