2022 LaserNetUS Users' Meeting
Notice bibliographique
Résumé
Organized and funded in 2018 through the US Department of Energy, Office of Fusion Energy Sciences (FES), LaserNetUS was created to provide vastly improved access to unique lasers for researchers. LaserNetUS is a network of ten high-power laser facilities, both academic and national laboratories, across the United States and Canada. These labs operate many of the premier mid- to large-scale high-intensity laser facilities in the US and Canada that are designed to be used in pioneering experimental studies in high energy density plasma and high field optical science. The network’s principal goal is to provide access to these state-of-the-art laser facilities to a broad range of researchers in the US and abroad. In its over four years of operation, LaserNetUS has awarded beamtime for over 60 user experiments to researchers from 25 different institutions. Over 400 user scientists, many of whom are students and post-docs, have participated in experiments at LaserNetUS facilities so far. The network now has over 1250 members. The LaserNetUS institutions are Colorado State University, Lawrence Berkeley National Lab, Lawrence Livermore National Lab, SLAC National Lab, The Ohio State University, University of Michigan, University of Nebraska-Lincoln, Institut National de la Recherche Scientifique, University of Rochester, and University of Texas at Austin. LaserNetUS hosted its first in-person Annual Users’ Meeting at Colorado State University in Fort Collins, CO, Aug 16-18, 2022. The meeting had 158 attendees, including 39 sponsored students and post-docs whose attendance and travel to the meeting were covered by DOE funds. Attendees included the 2018 Nobel Laureate in Physics, Donna Strickland. The program consisted of 5 plenary talks and several invited and contributed talks, a user community forum, a poster session, and built-in time for networking. The event focused on students and early career professionals. The poster session was held in combination with a reception to facilitate discussions and maximize interactions between the participants. The 39 sponsored students each presented a poster at the poster session, giving them valuable practice in sharing their research with others in the field. Many students and postdocs also gave talks during the main programming. Lunch and coffee breaks were provided for attendees for the duration of the conference on CSU’s campus. This allowed for networking among all participants. The building used to host the conference also had plenty of seating outside the auditorium, which was conducive to smaller one-on-one meetings and discussions between participants. There was also a lab tour of CSU’s Advanced Beam Laboratory. The day before and after the conference also included satellite meetings for the lab PIs and the Scientific Advisory Board. DOE support was used for rental of the auditorium and supporting rooms, student participation, 50% of the food costs, and transportation to the Advanced Beam Lab.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,000 |
| Communication savante | 0,005 | 0,003 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,405 | 0,373 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».