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A Fresh Look at Climate Change

2014· article· en· W11773208 sur OpenAlex

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aboutLe titre ou le résumé porte un signal canadien du lexique géographique.
no affAucune affiliation canadienne : ce travail est invisible pour une base fondée sur la seule affiliation.
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Notice bibliographique

RevueCato Journal · 2014
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueAtmospheric and Environmental Gas Dynamics
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésClimate changeWarrantGlobal warmingGlobal temperatureEconomicsClimatologyClimate modelQuarter (Canadian coin)Environmental scienceNatural resource economicsGeographyFinancial economicsEcology
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Recently The Economist (2013a), a prominent journalistic advocate of strong policies to control C[O.sub.2] emissions, expressed their puzzlement on the absence of warming over the last 15 years. They observed that this flat period of global average temperature occurred despite that C[O.sub.2] emissions from human sources continued at an increased rate. The total human-produced C[O.sub.2] emissions in that period of flat temperatures represent a quarter of all such emissions ever produced. The standard climate models, such as those used by the United Nation's International Panel on Climate Change (UN IPCC), anticipated that such massive C[O.sub.2] increases should have caused continuing increases in average global temperatures. The Economist noted that observed global average temperature is now at the lowest end of the predicted range, and that if the present trend continues, the actual temperatures will soon be below even the lowest forecasts. Most recently, Fyfe, Gillett, and Zwiers (2013) demonstrated that the current climate models have experienced a systematic failure--a finding very similar to Knappenberger and Michaels (2013). Given the large difference of observed data from the forecasts that underlie much current policy, it is timely to ask if the climate debates are addressing the right questions. Comparison of forecasts to observations is the right way to start asking. If the forecasts used to set policy are not accurate, then policies based on those forecasts warrant review. This is important for all of the purposes for which climate policies may be set, but this article concentrates on country development policies related to energy, especially electricity. Those policies are critical, because it is widely accepted that more than one billion people have no access to reliable electric grid power and therefore must turn to other sources for heat and light (Ballonoff 2013). The cost to provide that electricity, and also meet the continued and expanding needs of developed and developing countries, is estimated in the trillions of dollars. Our understanding of climate change and how it interacts with continued expansion of use of energy resources thus has a profound effect on assuring such huge capital cost is invested in the most effective way. The Status of Climate Science The foundation of the modern climate change discussion is the accurate observation that human activity has significantly increased the atmospheric concentration of C[O.sub.2], and that such activity is continuing (Tans 2009). Increased C[O.sub.2] concentration, especially when amplified by predicted feedback effects thus also is assumed to predict increasing global average atmospheric temperature. Depending on the degree of warming expected, other serious and mainly undesired effects are predicted. As The Economist (2013a) observed, the average global temperature did rise on average over the previous century. Following a 25-year cooling trend post-World War II, temperatures increased at an especially strong rate in the quarter century ending in 1997. The trend of that warming period, the correlation with increased C[O.sub.2], and the fact of human activity causing that C[O.sub.2] increase apparently supported use of projection models extending that trend to future years. Such projections were the basis for the UN's 1997 IPCC analysis on which much current policy is based. It is thus at least ironic that 1997 was also the last year in which such measured global average temperature increase took place. One of the key features of the IPCC forecast, and greenhouse effect forecasts generally, is the expected feedback loops. One of those is that the presumed drier and hotter conditions on the ground would cause expanded desertification and deforestation. A distinct kind of greenhouse effect is also predicted from increased C[O.sub.2] concentration--namely, the aerial fertilization effect, which is that plants grow better in an atmosphere of higher C[O. …

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,205
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0060,002

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.

Tête enseignante Opus0,009
Tête enseignante GPT0,198
Écart entre enseignants0,189 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle