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Record W7113436573

Full-Scale Slurry Tank Sampling: Effects of Sampling Strategy and Sample Storage on Measured Physical and Chemical Properties

2025· article· en· W7113436573 on OpenAlexfundno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMineral Processing and Grinding
Canadian institutionsnot available
FundersInterregAgencia Estatal de InvestigaciónEuropean Regional Development FundBundesamt für EnergieWageningen University and ResearchAgence de la transition écologiqueMinisterie van Economische Zaken en KlimaatMinistry of Science and ICT, South KoreaEuropean Agricultural Fund for Rural DevelopmentInnosuisse - Schweizerische Agentur für InnovationsförderungStaatssekretariat für Bildung, Forschung und InnovationRégion BretagneMinisterio de Asuntos Económicos y Transformación Digital, Gobierno de EspañaAgriculture and Agri-Food CanadaHainan UniversityNational Research FoundationVlaamse regeringNorges ForskningsrådBundesamt für UmweltNatural Sciences and Engineering Research Council of CanadaChina Scholarship CouncilRural Development AdministrationUniversidad Politécnica de MadridRegione LombardiaEmbrapa FlorestasMinistry of Agriculture, Forestry and FisheriesMajor Science and Technology Projects in Yunnan ProvinceNational Natural Science Foundation of ChinaNational Research Foundation of KoreaConselho Nacional de Desenvolvimento Científico e TecnológicoMinistry of EnvironmentChinese Academy of SciencesLietuvos Mokslo TarybaSvenska Forskningsrådet FormasCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorEuropean CommissionFundação de Amparo à Pesquisa do Estado de São PauloNatural Environment Research CouncilU.S. Department of AgricultureSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungTeagascNational Science FoundationMinistère de l'Agriculture, des Pêcheries et de l'AlimentationScience Foundation IrelandXunta de GaliciaInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du TravailAgroscopeGeraldine R. Dodge FoundationDepartment for Environment, Food and Rural Affairs, UK GovernmentNatural Resources Conservation ServiceGrønt Udviklings- og Demonstrations ProgramBundesamt für LandwirtschaftNational Institute of Food and AgricultureMinisterio de Ciencia, Innovación y UniversidadesFundação para a Ciência e a TecnologiaUniversità degli Studi di MilanoInnovationsfondenGrain Farmers of OntarioAgence Nationale de la RechercheBundesministerium für Ernährung und LandwirtschaftDepartment of Agriculture, Environment and Rural Affairs, UK GovernmentComunidad de MadridMinisteriet for Fø devarer, Landbrug og FiskeriBiotechnology and Biological Sciences Research CouncilMinisterio de Ciencia, Tecnología e Innovación ProductivaDepartment of Agriculture, Food and the Marine, IrelandMinisterio de Ciencia e InnovaciónNorthwestern UniversityInstituto Nacional de Investigación y Tecnología Agraria y Alimentaria
KeywordsSlurrySampling (signal processing)Sample (material)Storage tank
DOInot available

Abstract

fetched live from OpenAlex

evaluated by members of the Scientific Committee and the Organising Committee, resulting in the selection and allocation in oral presentations and poster presentations.This volume of abstracts contains only those abstracts that are expected to be actually presented at the conference.The Organising Committee takes no responsibility for any error and omission or for the opinions of the authors.This volume contains the selected abstracts as they were received.The Abstract Numbers in the TABLE OF CONTENTS are identification numbers.These abstract identification numbers are referred to from the Conference Programme Booklet, both for oral and poster presentations.For the oral presentations they are organised per parallel session.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.024
GPT teacher head0.245
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
Has abstractno

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