Notice bibliographique
Résumé
Conference Review This year’s Offshore Technology Conference (OTC), held 6-9 May in Houston, reflected the offshore oil sector’s health and energy, with attendance hitting a 30-year high and the event attracting top industry names from around the world. The globe’s largest offshore industry event attracted 104,800 people, the second highest in show history and up 17% from last year. Exhibitors represented 40 countries. Panel sessions, keynote speeches, and technical papers spanned the breadth and depth of the oil and gas industry. At one panel session, energy ministers and national oil company senior executives shared their perspectives on how the industry should adjust to address energy challenges as well as how the role of companies and governments should change to shape the future. The panel was moderated by Gamal Hassan, chief executive officer of ADHIG and OTC Program Chairman. The panel began with Jose de Vasconcelos, Angola’s Minister of Petroleum, who highlighted the connection between the need for energy and economic and social development. The industry faces many challenges in the quest to obtain energy security, which he defines as an equilibrium between supply and demand. Several challenges must be addressed to meet production needs: technologic, environmental, regulatory, and financial. Angola, he said, will maintain a permanent dialog with other producers to develop a common approach on energy and energy-related issues. David Ramsay, Minister of Industry, Tourism, and Investment, Northwest Territories, Canada, said that the role of government is to ensure that resources are “developed in a manner that brings economic development while ensuring the environment and its benefits” and at the same time working with industry and regulatory agencies to achieve this. Ramsay said that there is a renewed interest in the Arctic and northern Canada with opportunities onshore and offshore. The Canadian government is building infrastructure to assist in the transportation of fuels. Petrobras Chief Executive Officer Maria das Gracas Silva Foster said that exploration is a priority, and major investments that have been sustained over several years have resulted in the development of a diversified and competitive goods and services. Petrobras has benefited from a close association with universities to facilitate research in exploration and development, and the recent major discoveries as well as monetization of these reserves are a direct result of the investments in research and universities.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».