Bibliographic record
Abstract
From the start of the experimental activity of the Large Hadron Collider, Multiple Partonic Interactions (MPI) are experiencing a growing popularity and are widely invoked to account for observations that cannot be explained otherwise.This includes associated hadron production (Underlying Event) in high energy hadronic collisions with jets, the rates for multiple heavy flavor production, the survival probability of large rapidity gaps in hard diffraction, etc.In particular Double Parton Interactions were observed directly and studied by a number of the FNAL and LHC experiments in different reaction channels.At the LHC a new QCD regime has now been reached, where MPIs occur with high rates, in particular in central collisions, where the production of new particles is more likely to take place.Understanding MPIs is therefore crucial, both for their significant contribution to the background of various processes of interest for the search of new physics and because MPIs are an interesting topic of research by itself, allowing to probe high energy -high density QCD dynamics and, as a consequence of the geometrical characteristics of the interaction, to obtain unprecedented information on the correlated structure of the QCD bound states.The aim of this workshop is to provide an updated view of MPI studies, both experimental and theoretical, and to foster contacts between theoretical and experimental communities active in the field. TOPICS:• Phenomenology of MPI processes and multiparton distributions • Considerations for the description of MPI in QCD • Measuring multiple partonic interactions • Experimental results on inelastic hadronic collisions: underlying event, minimum bias, forward energy flow • Monte Carlo development and tuning • Connections with low x, diffraction, heavy ion physics and cosmic rays PARTICIPATIONScientists and students from all countries which are members of the United Nations, UNESCO or IAEA may attend the Workshop.As it will be conducted in English, participants should have an adequate working knowledge of that language.As a rule, travel and subsistence expenses of the participants should be borne by the home institution.Every effort should be made by candidates to secure support for their fare (or at least half-fare).However, limited funds are available for some participants who are nationals of, and working in, a developing country, and who are not more than 45 years old.Such support is available only for those who attend the entire activity.There is no registration fee.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.103 | 0.014 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".