Modern Analytical Facilities 2. A Review of Quality Assurance and Quality Control (QA/QC) Procedures for Lithogeochemical Data
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Quality assurance and quality control (QA/QC) are critical components of modern analytical geochemistry. A properly constructed QA/QC program identifies both the source of analytical error and provides a means of establishing confidence in and assessing limitations of analytical data. A QA/QC program involves monitoring precision, accuracy, and potential contamination from sampling to analysis. Precision can be monitored via the systematic insertion of sample, pulp, and analytical duplicates, and reference materials; the resulting data are subsequently evaluated using scatterplots, statistical tests (e.g. % relative standard deviation), Thompson-Howarth plots, and the average coefficient of variation (CVavg (%)). Accuracy is determined through the submission of reference materials and monitored using statistical tests (e.g. % relative difference, t-test) and Shewart control charts. Blanks test contamination and results are monitored using Shewart control charts.SOMMAIREL'assurance de la qualité et le contrôle de la qualité (AQ-CQ) sont deux composantes essentielles à la géochimie analytique moderne. Un programme AQ-CQ bien conçu défini à la fois la source de l'erreur d'analyse et un moyen d'établir la confiance et d’évaluer les limites des données analytiques. Un programme AQ-CQ comprend le contrôle de la précision, de l'exactitude et de la contamination potentielle, de l'étape d’échantillonnage à l'analyse. La précision peut être contrôlée via l'insertion systématique d'échantillon, de pulpes, et de doublons d'analyse, et de matériaux de référence; les données obtenues sont ensuite évaluées en utilisant des diagrammes de dispersion, des tests statistiques (pourcentage d’écart type relatif, par ex.), des courbes de Thompson-Howarth, et des coefficients de variation moyens (CVm %). La précision est déterminée par la soumission de documents de référence et de contrôle par des tests statistiques (différence relative en %, t-test, par ex.) et des graphiques de contrôle de Shewhart. La contamination d’essais à blanc et les résultats sont contrôlés par des graphiques de contrôle Shewhart.
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.
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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.001 |
| 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 it