High-density, high quality regional sampling of water supply wells: Ontario's ambient groundwater geochemical program
Notice bibliographique
Résumé
The Ambient Groundwater Geochemistry (AGG) initiative of the Ontario Geological Survey is a regional high density groundwater sampling program, the purpose of which is to map and understand the existing groundwater geochemical conditions in Ontario's major rock and surficial sediment aquifers. Throughout the last decade, the study has amassed data for 2664 samples from 2095 stations across 96,000 km2 representing all of southern Ontario. This one-time sampling program relies on existing well infrastructure sampled in a 10x10 km grid pattern. Monitoring and farm wells are used but the majority are domestic water supply wells with purging and sampling protocols adapted to the well type. Sites are randomly selected such that three criteria are met: (1) the water source must be determined, (2) the full, untreated geochemical matrix must be characterized (3) data quality must be assured; i.e. it must be demonstrated that what was intended to be measured has been correctly measured. A combination of field protocols, laboratory methods and a post acquisition QC auditing process, which collectively last for 6 months beyond a typical field season. Wells are selected only if their well construction details can be ascertained and cross-checked. The sources, and therefore reliability, of this information are recorded in the database and used later in an audit of all station information collected in the field. The audit, which uses well logs, field notes, well owner comments, continuous logs of field parameters (temperature, pH, etc) and field photos, typically lasts several months and scrutinizes well construction details, well-head security, plumbing details, integrity of water source and the geological origin of the water. In most years, based on the audit, a small number of sampled waters do not meet one of the three criteria and are rejected for inclusion in the AGG database. Analytical QC/QA procedures are rigorous. At least two analytical techniques are used to analyze many of the important parameters including the major ions, nitrate, iodide and many metals and these redundant analyses are checked against each other. Blind field duplicates, blanks and multiple reference standards are inserted at regular intervals in lab submissions and amount to 15% of all samples submitted and are used to confirm precision and accuracy for all parameters. Where data are found to fail the quality assurance tests, mitigation action is taken that may include re-analysis, resampling, or at worst, removal of the problem samples from the database. These techniques provide the quality assurance required for publication of the database. All blind quality control data are published, along with 27 station attributes, which allows end-users many options in the way they use the data, including creating subsets of the data for particular uses. The breadth of analysis, uniformity of coverage, areal extent and data quality of this dataset together far exceeds that of any previously existing groundwater geochemical databases in the province of Ontario.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,005 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».