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Record W1872696227 · doi:10.1007/s11433-015-5778-0

Physics perspectives of heavy-ion collisions at very high energy

2016· article· en· W1872696227 on OpenAlexafffund
Ning-Bo Chang, Shanshan Cao, Baoyi Chen, Shiyong Chen, Zhen‐Yu Chen, Heng-Tong Ding, M. He, Zhi‐Quan Liu, Long-Gang Pang, Guang-You Qin, Ralf Rapp, Björn Schenke, Chun Shen, Huichao Song, H. Xu, Qun Wang, Xin-Nian Wang, Benwei Zhang, Han‐Zhong Zhang, Xiangrong Zhu, Pengfei Zhuang

Bibliographic record

VenueScience China Physics Mechanics and Astronomy · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicHigh-Energy Particle Collisions Research
Canadian institutionsMcGill University
FundersNuclear PhysicsNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaDeutsche ForschungsgemeinschaftU.S. Department of EnergyOffice of ScienceNational Science Foundation
KeywordsPhysicsJet quenchingPartonQuark–gluon plasmaNuclear physicsPlasmaParticle physicsHeavy ionColliderDissociation (chemistry)High energyStrange matterRelativistic Heavy Ion ColliderIonQuark

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 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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.738
Threshold uncertainty score0.777

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.010
GPT teacher head0.252
Teacher spread0.242 · 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 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

Citations21
Published2016
Admission routes2
Has abstractno

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