Notice bibliographique
Résumé
Abstract The convergence of increasing concern about energy supply and increasing public commitment to environmental protection provides an opportunity to mobilize public and private investment in energy innovation. To tap the vast Canadian resource potential, innovative new technologies are required-to unlock the large remaining conventional oil and gas reserves, take advantage of the hundreds of years of remaining production of bitumen, coal, and coal bed methane, and ensure increasing supply from renewable energy options. As Alberta's energy innovation strategy was developed, recognition grew that solutions to the pressing challenges described above emerge when we understand the energy industry as one interconnected system, integrated horizontally along the various energy sources and vertically along the value chain. This led to the creation of the Energy Innovation Network (EnergyINet) as the vehicle to facilitate strategic collaboration and innovation among industry, governments (federal and provincial), and the research community to address the challenges of ensuring an abundant supply of environmentally responsible energy. This paper describes, as an example, the approach taken in the development of oil sands technologies where a government-industry partnership was developed to share resources, build expertise, and lower technology risks. This provided the key tools that have lead to the oil sands becoming a significant resource relative to global energy demand. The paper argues that no one single source of energy will be sufficient to meet world or Canadian demand and consequently for the need for a collaborative initiative to facilitate a long-term (20- to 25-year) effort to implement an integrated energy innovation strategy. This integrated approach is built on the premise that strategic investment in a balanced portfolio of energy innovation "with a focus on common technology platforms and points of leverage across the portfolio" has the greatest potential for returns in economic, environmental, and social terms. Introduction The International Energy Agency (IEA) projects that global primary energy demand will increase by 1.7% per annum from 2000 to 2030, reaching an annual level of 15.3 billion tonnes of oil equivalent. The increase will be equal to two thirds of current demand(1). The world will remain heavily reliant on traditional forms of energy. Though renewables are expected to grow from a low base, they cannot displace fossil fuels as the overriding source of energy in this time scale. Fossil fuels are expected to supply over 90% of global incremental energy demand through 2030. Gas consumption is estimated to double between 2000 and 2030 in view of its cost competitiveness, ample availability, and environmental advantages. Oil will remain the largest fuel source with demand increasing by 1.6% per annum. Canada is the 5th largest energy producer in the world and is a net exporter of energy; these exports account for about 7% of the GDP. Canada is also a world leader in hydroelectric power development (24% of domestic consumption), but there is limited potential for development of new hydroelectric sites. Nuclear energy (5% of domestic consumption) is declining, and there have been no investments in new nuclear facilities for nearly 20 years.
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 | 0,015 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,006 | 0,006 |
| Communication savante | 0,011 | 0,011 |
| Science ouverte | 0,002 | 0,012 |
| Intégrité de la recherche | 0,008 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,001 |
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 ».