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Enregistrement W4364375599 · doi:10.1029/2023cn000210

Frontier of Understanding Earth's Dynamics

2023· article· en· W4364375599 sur OpenAlexaboutno aff
H. Watanabe, Natsue Abe, W. F. McDonough, Tamano Omata, Yasuhiro Yamada

Notice bibliographique

RevuePerspectives of Earth and Space Scientists · 2023
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueMethane Hydrates and Related Phenomena
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBiosphereEarth scienceObservatoryNASA Deep Space NetworkGeologyPhysicsAstronomySpacecraft

Résumé

récupéré en direct d'OpenAlex

Innovations in technology drive science. In August 2022 and January 2023, Tohoku university and Japanese Agency for Marine-Earth Science and Technology hosted two international, multidisciplinary workshops highlighting the importance of technological developments for bringing new insights into science (https://www.tfc.tohoku.ac.jp/event/4288.html and https://www.tfc.tohoku.ac.jp/event/4294.html). The diverse team of participants covered areas, such as deep ocean drilling and ocean floor measurement, insights from machine learning, discovering more of and understanding the Earth's deep biosphere, findings from Hayabusa, measuring the Earth's geoneutrino flux, minerals as a recorder of Earth's exposure to dark matter, and more. In addition, there was a well attended, separate outreach program that included a celebration day at the Sendai Astronomical Observatory complete with two public lectures and display booths on technologies for science. This eclectic mix of science achieved through the use of the latest technology, lead to useful, cross disciplinary insights and discussions. Concepts of various Earth systems and feedbacks between systems were highlighted. For example, the deep biosphere, hosted in photon-deprived, kilometer-deep domains in the lithosphere, are nurtured (e.g., water radiolysis) by energetic particles from alpha and beta decays, produced by the surrounding rocks, and cosmic ray produced muons. Deep scientific drilling also revealed that processes controlling Earth's evolution also support its deep biosphere. Ushering in a new era of multi-messenger geophysics, particle physicists reminded us of the flux of neutrinos and antineutrinos showering the Earth from above and below, respectively, while others consider the potential of recording Earth's exposure to dark matter particles. Seismologists and geodesists reported on their current and future efforts to instrument the highly active Japan trench immediately to the east. Ongoing physics experiments reported on the detection of the Earth's flux of geoneutrinos, chargeless and near massless ghost particles emitted during naturally occurring, beta-minus decay. Sited in the Archean craton of Canada and the Phanerozoic crust of Japan, these active detectors are revealing Earth's radiogenic heating potential and its abundances of thorium and uranium, all through the filter of their continental lithospheres. A proposal to deploy a similar detector in the deep ocean was presented, as it allows for filter-free, chemical mapping of the Earth's interior, a neutron-quiet sensor for dark matter, and a low energy monitor of galactic stellar explosions. Dark matter scientists reviewed their developments of automated technologies that rapidly map out sub-to-micron scale volumes in low radioactive minerals (e.g., olivine). This technology drives their search of fission-like tracks resulting from rare interactions of dark matter with these terrestrial minerals (https://arxiv.org/abs/2301.07118). These scientists identified the importance of accessing fresh, unaltered minerals that have a well define and low temperature history (e.g., deep drill core samples of ancient oceanic crust). New insights from machine learning efforts promises to enhance substantially data integration and interpretation. We were reminded that recognizing complex patterns and building predictive models from big data requires this new applied technology to overcome the obvious challenges of big geoscientific data analysis (i.e., the volume, velocity, variety and veracity of big geo-data). Collaborations with machine learning experts and geoscientists will advance our understandings of a wide range of Earth system science. Geodynamicists are readily absorbing new advances in understanding the planet's dynamics as revealed by these many technological developments. Incorporating these insights into models of Earth's evolution are shaping the outcomes. Innovations in determining mineral properties at high temperatures and high pressures are leading to more accurate insights in the thermal history and viscosity profile of the planet. Increasingly, from the depths of the inner core to the near surface of an oceanic trench, seismologists are imaging the Earth's interior with greater resolution and capturing its dynamic processes in action, not just at the plate subduction interface. However, we are vexed to constrain superstructures in the deep mantle as remnants of the planet's early differentiation or developments from the more modern process of plate tectonics. Planetary scientists are venturing beyond the Earth and gaining insights into the Moon, Mars, Ryugu, and other Solar system bodies. Consequently, these missions are bringing refreshingly new understandings of Earth's origin and evolutionary processes. Angst was, however, expressed given our superior understanding of the surface of the Moon and Mars that stands in contrast with that of our own seafloor. Exploitation of potential resources on the Earth's seafloor or other planetary bodies require a better understanding of what is there. Excitement from the primitive return samples delivered by Hayabusa2 gave us an unparalleled insight into the building blocks of the planets and its organic constituents. The rich inventory of volatiles and organic compound found in Ryugu samples stand in contrast to our most primitive meteorites that are dramatically depleted by their passage through the atmosphere. The origin and evolution of asteroidal rubble piles (e.g., Ryugu) and their shifting positions in the Solar system are revealing the timing and dynamics of the wanning stages of the accretion disk and the jockeying of the gas giant planets. The questions of where, why, and how life originates, survives, and evolves were asked by scientists interested in the deep biosphere. It was highlighted that the term “deep” needs to be recognized in the dimension of time, space, and condition to appreciate the full potential of possibilities. Understanding the perceived limits of life on Earth and elsewhere challenges our biases regarding the ecology of habitability. Advances in ocean drilling was a highlight. Although Hayabusa2 returned extraterrestrial samples from Ryugu, we have yet to return intact mantle samples from below the Moho. Biological and geological exploration of the seafloor and its subsurface remain a significant research target for both fundamental and applied science. We continue to reveal new insights into Earth's deep biosphere that extends kilometers beneath the seafloor, made possible through scientific drilling. Drilling to the mantle remains a yet to be achieved goal more than 50 years on. The dynamics of mantle plumes rising from the core-mantle boundary to erupting on the seafloor were exposed by drilling of submerged large oceanic platforms. Development of warning systems in offshore, seismogenic zones was featured with Japan's Dense Oceanfloor Network System for Earthquakes and Tsunamis. All of these exploration demands represent continuing and new challenges for underwater technologies. New technologies are highways to new insights. Removing disciplinary barriers and enjoying the company of new friends produced exciting new ideas. Particle physicists, biochemists, engineers, and machine-learning specialists were excited by the complexities and opportunities offered by the geoscience community. The next 10–20 years will bring new opportunities and new insights, particularly if we break down the barriers of science. The drivers of science will exist on the edges between disciplines. This work was supported by the Tohoku Forum for Creativity via the thematic program “Frontier of Understanding Earth’s Interior and Dynamics”.

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 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 candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,271
Score d'incertitude au seuil0,586

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,014
Tête enseignante GPT0,231
Écart entre enseignants0,217 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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Même revuePerspectives of Earth and Space ScientistsMême sujetMethane Hydrates and Related PhenomenaTravaux en français237 207