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Record W2625559578 · doi:10.1016/j.ppnp.2018.01.006

NuSTEC  White Paper: Status and challenges of neutrino–nucleus scattering

2018· article· en· W2625559578 on OpenAlexafffund

Bibliographic record

VenueProgress in Particle and Nuclear Physics · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNeutrino Physics Research
Canadian institutionsPerimeter Institute
FundersH2020 Marie Skłodowska-Curie ActionsNuclear PhysicsOntario Ministry of Research and InnovationEuropean Regional Development FundHorizon 2020Japan Society for the Promotion of ScienceScience and Technology Facilities CouncilHorizon 2020 Framework ProgrammeOffice of ScienceVlaamse regeringNarodowe Centrum NaukiFonds Wetenschappelijk OnderzoekVirginia Polytechnic Institute and State UniversityIstituto Nazionale di Fisica NucleareFermilabBelgian Federal Science Policy OfficeGovernment of CanadaGeneralitat ValencianaCommissariat à l'Énergie Atomique et aux Énergies AlternativesMinisterio de Economía y CompetitividadColorado State UniversityUniversity of PittsburghU.S. Department of EnergyUniversità degli Studi di TorinoMichigan State UniversityMinistry of Education, Culture, Sports, Science and TechnologyInnovation, Science and Economic Development CanadaNorthwestern UniversityCollege of Engineering, Michigan State UniversityUniversity of WashingtonAlfred P. Sloan FoundationInstituto Nazionale di Fisica NucleareMassachusetts Institute of TechnologyEuropean Commission
KeywordsObservableScatteringEvent (particle physics)Oscillation (cell signaling)NeutrinoNeutrino oscillation

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.017
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0060.004
Scholarly communication0.0110.011
Open science0.0030.007
Research integrity0.0150.010
Insufficient payload (model declined to judge)0.0200.012

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 head0.032
GPT teacher head0.294
Teacher spread0.262 · 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 designTheoretical or conceptual
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

Citations316
Published2018
Admission routes2
Has abstractno

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