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Record W7095127806

McGill/00-04 OITS-686 Particle Multiplicities and Thermalization in High Energy Collisions

2000· article· en· W7095127806 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicGenital Health and Disease
Canadian institutionsnot available
Fundersnot available
KeywordsThermalisationHadronAmplitudeParticle (ecology)Distribution (mathematics)High energyQuantum chromodynamicsProduction (economics)PhotonBoltzmann constant
DOInot available

Abstract

fetched live from OpenAlex

We investigate the conditions under which particle multiplicities in high energy collisions are Boltzmann distributed, as is the case for hadron production in e + e − , pp, p¯p and heavy ion collisions. We show that the apparent temperature governing this distribution does not necessarily imply equilibrium (thermal or chemical) in the usual sense, as we explain. We discuss an explicit example using tree level amplitudes for N photon production in which a Boltzmann-like distribution is obtained without any equilibration. We argue that the failure of statistical techniques based on free particle ensembles may provide a signal for collective phenomena (such as large shifts in masses and widths of resonances) related to the QCD phase transition.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.132
Threshold uncertainty score0.441

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1320.011

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 head0.014
GPT teacher head0.263
Teacher spread0.249 · 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 designBench or experimental
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

Citations0
Published2000
Admission routes1
Has abstractyes

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