PANIWATER: Risk in Water Management Workshop presentations (Dec '23)
Bibliographic record
Abstract
Version 1.0.0 This archive contains the presentation given by the invited speakers for the workshop "Risk in Water Management", held on December 13th 2023 in Rome, organised by the Horizon 2020 project PANIWATER (Grant Agreement N° 820718) Presentations inlcuded in this archive version are 1-Circular economy solutions for Wastewater Resource Management - Rita Dhodapkar (CSIR-NEERI)3-The general risk assessment framework applied to water contamination - Emanuela Testai (Istituto Superiore di Sanità - ISS)4-Wastewater reuse in Apulia Region: a best practice approach to governance challenges - Roberta Rana (Autorità Idrica Pugliese)5-Water Safety Plans: the experience of Acque Bresciane - Michela Biasibetti6-Funding opportunities in Horizon Europe - Fabio Ugolini7-Anaerobic process as mainstream treatment option for urban wastewater - Concetta Tomei8a-Novel advanced oxidation processes for controlling known and unknown micropollutants in wastewater: treatment strategies - Domenico Santoro 8b-Novel advanced oxidation processes for controlling known and unknown micropollutants in wastewater: online and real-time control by fluorescence - Paolo Roccaro9-Interaction between microplastics and antibiotic-resistant bacteria in water: Effect on disinfection performance - Kyriakos Manoli Presentations not included in this archive version are2-Risk assessment methods, hazard identification, environmental risks and public health implications - Pawan Labhasetwar In addition are included:- a pdf file with the meeting agenda and the speakers short bios- a pdf file with the poster used to advertise the event for info, please contact: innova@paniwater.eu
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.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.592 | 0.392 |
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".