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Record W4234701459 · doi:10.2172/1638864

APS Science 2019 Volume 2: Research and Engineering Highlights from the Advanced Photon Source at Argonne National Laboratory

2020· report· en· W4234701459 on OpenAlexfundno aff
Richard B. Fenner

Bibliographic record

Venuenot available
Typereport
Languageen
FieldPhysics and Astronomy
TopicAdvanced X-ray Imaging Techniques
Canadian institutionsnot available
FundersArgonne National LaboratoryArmy Research OfficeDivision of ChemistryDivision of Electrical, Communications and Cyber SystemsBrookhaven National LaboratoryDivision of Materials ResearchGeoffrey Beene Cancer Research CenterNational Institute of Diabetes and Digestive and Kidney DiseasesOffice of Naval ResearchLos Alamos National LaboratoryNational Institute of General Medical SciencesOffice of Research Infrastructure Programs, National Institutes of HealthWestern Economic Diversification CanadaMaterials Research Science and Engineering Center, Harvard UniversityAmerican Chemical Society Petroleum Research FundNational Nuclear Security AdministrationOffice of ScienceUniversity of Illinois at Urbana-ChampaignNational Institutes of HealthShanghaiTech UniversityNational Natural Science Foundation of ChinaBiological and Environmental ResearchUniversity of Chinese Academy of SciencesDavid and Lucile Packard FoundationUniversity of ChicagoConsejo Nacional de Ciencia y TecnologíaDeutsche ForschungsgemeinschaftChinese Academy of SciencesU.S. Department of EnergyDeutsches Elektronen-SynchrotronScience Fund for Creative Research GroupsSLAC National Accelerator LaboratoryWashington State UniversityHarvard UniversityTürkiye Bilimsel ve Teknolojik Araştırma KurumuArkansas NSF EPSCoRVillum FondenNatural Sciences and Engineering Research Council of CanadaOffice of Experimental Program to Stimulate Competitive ResearchNorthwestern UniversityDuPontOffice of Energy EfficiencyDow Chemical CompanyNational Institute of Allergy and Infectious DiseasesMemorial Sloan-Kettering Cancer CenterNational Cancer InstituteCamille and Henry Dreyfus FoundationU.S. Department of TransportationNational Science Fund for Distinguished Young ScholarsOffice of Energy Efficiency and Renewable EnergyNational Science FoundationBasic Energy SciencesU.S. Department of Health and Human ServicesFederal Highway AdministrationU.S. Department of Defense
KeywordsNational laboratoryAdvanced Photon SourceCoronavirus disease 2019 (COVID-19)Library scienceWork (physics)Science and engineeringPandemicVolume (thermodynamics)EngineeringComputer scienceEngineering physicsEngineering ethicsPhysicsMechanical engineeringMedicineCivil engineeringParticle accelerator

Abstract

fetched live from OpenAlex

This issue of our bi-annual highlights roundup includes a bit of time shifting. The book features a second batch of articles looking back on the calendar year 2019 work of our incomparable users and staff, but included also are some science highlights and other content driven by the COVID-19 pandemic.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.602
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.322
Teacher spread0.295 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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