Report on the development and testing of new reference methods employing selected GMOS ground-based master sites
Bibliographic record
Abstract
Mercury (Hg) is a global pollutant of concern due to its toxicity and bioaccumulation in aquatic food chains with serious consequences on human and wildlife health. Although in the past two decades a number of Hg monitoring sites have been established in Europe, Canada, USA and Asia as part of regional network the need of long-term atmospheric Hg monitoring and additional ground-based monitoring sites have constantly been highlighted to generate consistent datasets necessary for offering new insight and information about the global scale trends of atmospheric Hg emissions and deposition. A coordinated global observational network for atmospheric Hg has been established in the framework of the Global Mercury Observation System (GMOS) project (FP7) in 2010 with the aim to provide high-quality Hg datasets in the Northern and Southern Hemispheres for a comprehensive assessment of atmospheric Hg concentrations and their dependence on meteorology, long-range atmospheric transport and atmospheric emissions on a global scale. Hg measurements were carried out using high-quality techniques by harmonizing the chosen measurement techniques with those being performed at existing monitoring stations around the world. Special attention was paid in respect to protocols harmonization, data quality collection and data management in order to assure a full comparability of site specific observational datasets. During the planning and implementation stage of the GMOS global network, harmonized Standard Operating Procedures (SOPs) as well as common Quality Assurance/Quality Control (QA/QC) protocols have been indeed addressed in accordance with the measurement practice adopted in well-established regional monitoring networks and based on the most recent literature. A great effort was in particular made to implement a centralized system (termed GMOS-Data Quality Management, G-DQM) able to acquire atmospheric Hg data in near real-time and, furthermore, to assure and control quality of collected Hg datasets. This system introduced a big novelty for data control programs, consisting in a service approach that facilitate real-time adaptive monitoring procedures, thus being essential in preventing the production of poor-quality data. The Deliverable 1.2.5 provides a report detailing GMOS methods adopted within the global network.
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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 | 0.013 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.006 |
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".