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Record W4364375599 · doi:10.1029/2023cn000210

Frontier of Understanding Earth's Dynamics

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

Bibliographic record

VenuePerspectives of Earth and Space Scientists · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsBiosphereEarth scienceObservatoryNASA Deep Space NetworkGeologyPhysicsAstronomySpacecraft

Abstract

fetched live from 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”.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.271
Threshold uncertainty score0.586

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.231
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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