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Preface

2020· article· en· W4244478135 on OpenAlexaboutno aff

Bibliographic record

VenueJournal of Physics Conference Series · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum, superfluid, helium dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsThursdayScheduleSession (web analytics)Library sciencePhysicsComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

The 15 th edition of the International Conference on Topics in Astroparticle and Underground Physics (TAUP 2017) was held from July 24 through 28, 2017 in Sudbury, Ontario Canada. It was organized and hosted by Laurentian University and SNOLAB with sponsorship and other support from the City of Greater Sudbury, IOP Publishing, the Institute of Particle Physics, the International Union of Pure and Applied Physicists, and Vale. The meeting attracted 350 participants from around the world: 31 countries were represented. The topics discussed at the meeting included Cosmology, Dark Matter, Neutrino Physics and Astrophysics, Gravitational Waves, High-Energy Astrophysics and Cosmic Rays, New Technologies, and the intersection of these fields. We were particularly pleased to open the meeting with a discussion of education, outreach, and inclusion and to have these themes continue throughout the week. List of TAUP 2017 Organizing Committee, TAUP-2017 International Advisory Committee, TAUP Steering Committee, Conference Schedule: Monday, July 24, Conference Schedule: Tuesday, July 25, Conference Schedule: Wednesday, July 26, Conference Schedule: Thursday, July 27, Conference Schedule: Friday, July 28, Poster Session, Monday Parallel Sessions: 1:00 PM - 3:00 PM, Monday Parallel Sessions: 3:30 PM - 5:30 PM, Tuesday Parallel Sessions: 1:00 PM - 3:00 PM, Tuesday Parallel Sessions: 3:30 PM - 5:30 PM, Wednesday Parallel Sessions: 1:00 PM - 3:00 PM, Wednesday Parallel Sessions: 1:00 PM - 3:00 PM, Wednesday Parallel Sessions: 3:30 PM - 5:30 PM, Wednesday Parallel Sessions: 3:30 PM - 5:30 PM, Thursday Parallel Sessions: 1:00 PM - 3:00 PM, Thursday Parallel Sessions: 3:30 PM - 5:30 PM are available in the pdf.

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 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 score0.531
Threshold uncertainty score0.588

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.024
GPT teacher head0.237
Teacher spread0.213 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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