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The China Jinping Underground Laboratory and Its Early Science

2017· article· en· W2224965353 on OpenAlexaff
Jianping Cheng, Kejun Kang, Jianmin Li, Jin Li, Yuanjing Li, Qian Yue, Zhi Zeng, Yunhua Chen, Shiyong Wu, Xiangdong Ji, H. T. Wong

Bibliographic record

VenueAnnual Review of Nuclear and Particle Science · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDark Matter and Cosmic Phenomena
Canadian institutionsInstitute of Particle Physics
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of ChinaMinistry of Education of the People's Republic of ChinaNational Science Foundation
KeywordsOverburdenChinaPhysicsNuclear physicsMining engineeringNuclear engineeringArchaeologyEngineeringGeography

Abstract

fetched live from OpenAlex

The China Jinping Underground Laboratory, inaugurated in 2010, is an underground research facility with the deepest rock overburden and largest space by volume in the world. The first-generation science programs include dark matter searches conducted by the CDEX and PandaX experiments. These activities are complemented by measurements of ambient radioactivity and the installation of low-background counting systems. Phase II of the facility is being constructed, and its potential research projects are being formulated. In this review, we discuss the history, key features, results, and status of this facility and its experimental programs, as well as their future evolution and plans.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0020.002
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.003

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 head0.010
GPT teacher head0.284
Teacher spread0.273 · 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 designNot applicable
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

Citations125
Published2017
Admission routes1
Has abstractyes

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