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Record W4297819896 · doi:10.23731/cyrm-2017-003.441

Chapter 3: Beyond the Standard Model Phenomena

2017· article· en· W4297819896 on OpenAlexfundno aff
T. Golling

Bibliographic record

VenueCERN Document Server (European Organization for Nuclear Research) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Science and Diplomacy
Canadian institutionsnot available
FundersBasic Energy SciencesOffice of ScienceNatural Sciences and Engineering Research Council of CanadaInstitut Périmètre de physique théoriqueInstitució Catalana de Recerca i Estudis AvançatsMinistero dell’Istruzione, dell’Università e della RicercaUniversità degli Studi di PadovaArgonne National LaboratoryIndustry CanadaFonds De La Recherche Scientifique - FNRSIsrael Science FoundationUnited States-Israel Binational Science FoundationJohn Simon Guggenheim Memorial FoundationMinistero dello Sviluppo EconomicoPlanning and Budgeting Committee of the Council for Higher Education of IsraelDanmarks GrundforskningsfondGovernment of CanadaDeutsche ForschungsgemeinschaftScience and Technology Facilities CouncilNational Research FoundationU.S. Department of EnergyEuropean CommissionFermilabUniversity of MinnesotaNational Science FoundationSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsStandard Model (mathematical formulation)Computer scienceMaterials scienceMetallurgy

Abstract

fetched live from OpenAlex

This chapter summarises the physics opportunities in the search and study of physics beyond the Standard Model at the 100 TeV pp collider.

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)0.001
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: Theoretical or conceptual
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0040.005
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0210.004

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 head0.052
GPT teacher head0.347
Teacher spread0.294 · 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
GenreReview

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

Citations47
Published2017
Admission routes1
Has abstractyes

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Same venueCERN Document Server (European Organization for Nuclear Research)Same topicInternational Science and DiplomacyFrench-language works237,207