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Record W605158062

Intersections of Particle and Nuclear Physics : 7th conference CIPANP2000, Quebec City, Canada, 22-28 May, 2000

2000· book· en· W605158062 on OpenAlexaboutno aff
Z. Parsa, William J. Marciano

Bibliographic record

VenueAmerican Institute of Physics eBooks · 2000
Typebook
Languageen
FieldPhysics and Astronomy
TopicNuclear physics research studies
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsQuantum chromodynamicsParticle physicsQuarkHadronNuclear physicsPhysics beyond the Standard Model
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this meeting, as with six previous conferences in this series, was to bring together particle and nuclear physicists to share scientific reports and discuss areas of research which overlap both disciplines. The need for such an interdisciplinary conference was recognized by Alan D. Krisch and Malcolm H. MacFarlane, founding fathers of CIPANP series. Its relevance has steadily grown as areas of overlap between particle and nuclear physics have increased. In addition, success of standard model has provided a common underpinning for both disciplines as well as similar fundamental goals. Indeed, Quantum Chromodynamics (QCD) has proven to be the theory of strong interactions. As such, it forms basis for nuclear physics as well as high energy hadronic interactions. Topics included are: QCD spectroscopy and dynamics, relativistic heavy ions, QCD and nuclear structure, lepton-hadron and hadron-hadron scattering, heavy quark and heavy lepton physics, spin physics, nuclear and particle astrophysics, neutrinos, accelerators, facilities and detectors, as well as tests of fundamental symmetries.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.378
Threshold uncertainty score0.760

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0040.001
Scholarly communication0.0050.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.1400.042

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 head0.021
GPT teacher head0.257
Teacher spread0.235 · 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
GenreOther

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

Citations2
Published2000
Admission routes1
Has abstractyes

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