Notice bibliographique
Résumé
The 2021 2nd International Conference on Geology, Mapping and Remote Sensing (ICGMRS 2021) was be held virtually online on April 23-25, 2021 due to the precaution taken to minimizing the COVID-19 risk. The safety and well-being of all conference participants was our first and top priority, while we strived to offer many scholars and researchers this long-awaited conference to conduct academic exchanges with their peers. ICGMRS 2021 is to bring together innovative academics and industrial experts in the field of geology, mapping and remote sensing to a common conference. The primary goal of the conference is to promote research and developmental activities in geology, mapping and remote sensing and another goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working all around the world. The COVID-19 virus has made our life very challenging, but we want to reiterate that there are no barriers to science, as we continue to do our research works via modern technical means. The ICGMRS 2021 has selected Zoom as the virtual platform. Each presenter will be given a 15-minute talk and followed by a short discussion afterward. Before the conference, all of the authors were encouraged to submit a video as a backup in case of unexpected technical problems. There were 140 individuals who attended this on-line conference, represented many countries including China, Canada, South Korea, Singapore and UK. During the conference, we invited three professors as our keynote speakers. A. Prof. Chao Chen, from Zhejiang Ocean University, performed a speech: Spatio-temporal pattern evolution of coastlines for archipelagic regions. His research area is Marine Environment Remote Sensing. And then we had A. Prof. Heng Dong, from Wuhan University of Technology. He delivered a speech: Estimation of Global Terrestrial Gross Primary Productivity based on Solar-Induced Chlorophyll Fluorescence. In this study, after analyzing the fluorescence emission mechanism at different spatial scales, and the GPP-SIF empirical linear estimation model, some factors affecting the photosynthetic capacity of the vegetation and the canopy SIF emission were introduced to construct a new GPP estimation method. Lastly, we were glad to invite A. Prof. Xuemin Xing, from Changsha University of Science & Technology as our finale keynote speakers. She shared a speech: Measuring subsidence over soft clay highway based on a novel time-series InSAR deformation model: with emphasis on rheological properties and seasonal factors. Their insightful speeches had triggered heated discussion of the conference. Every participant praised this conference for disseminating useful and insightful knowledge. The proceedings are a compilation of the accepted papers and represent an interesting outcome of the conference. Topics include but are not limited to the following areas: Geography & Geology, Surveying & Mapping, Remote Sensing, Application of Remote Sensing Technology and other related topics. All the papers have been through rigorous review and process to meet the requirements of International publication standard. We would like to acknowledge all of those who supported ICGMRS 2021. The help and contribution of each individual and institution was instrumental in the success of the conference. In particular, we would like to thank the organizing committee for its valuable inputs in shaping the conference program and reviewing the submitted papers. The Committee of ICGMRS 2021 Committee member, Conference Chair, Program Committees, Technical Program Committees and this titles are available in this pdf.
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 | 0,002 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,005 | 0,004 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,549 | 0,404 |
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 ».