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Submarine Landslides and Their Tsunami Hazard

2021· article· en· W3139255971 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAnnual Review of Earth and Planetary Sciences · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsnot available
FundersBritish Geological SurveyNatural Environment Research CouncilSight Research UKEuropean Space Agency
KeywordsSubmarine landslideLandslideGeologySubmarine pipelineSeismologyContext (archaeology)HazardNew guineaSubmarineOceanographyPaleontologyHistory

Abstract

fetched live from OpenAlex

Most tsunamis are generated by earthquakes, but in 1998, a seabed slump offshore of northern Papua New Guinea (PNG) generated a tsunami up to 15 m high that killed more than 2,200 people. The event changed our understanding of tsunami mechanisms and was the forerunner to two decades of major tsunamis that included those in Turkey, the Indian Ocean, Japan, and Sulawesi and Anak Krakatau in Indonesia. PNG provided a context to better understand these tsunamis as well as older submarine landslide events, such as Storegga (8150 BP); Alika 2 in Hawaii (120,000 BP), and Grand Banks, Canada (1929), together with those from dual earthquake/landslide mechanisms, such as Messina (1908), Puerto Rico (1928), and Japan (2011). PNG proved that submarine landslides generate devastating tsunamis from failure mechanisms that can be very different, whether singly or in combination with earthquakes. It demonstrated the critical importance of seabed mapping to identify these mechanisms as well as stimulated the development of new numerical tsunami modeling methodologies. In combination with other recent tsunamis, PNG demonstrated the critical importance of these events in advancing our understanding of tsunami hazard and risk. This review recounts how, since 1998, understanding of the tsunami hazard from submarine landslides has progressed far beyond anything considered possible at that time. ▪ For submarine landslide tsunamis, advances in understanding take place incrementally, usually in response to major, sometimes catastrophic, events. ▪ The Papua New Guinea tsunami in 1998, when more than 2,200 people perished, was a turning point in first recognizing the significant tsunami hazard from submarine landslides. ▪ Over the past 2 to 3 years advances have also been made mainly because of improvements in numerical modeling based on older tsunamis such as Grand Banks in 1929, Messina in 1908, and Storegga at 8150 BP. ▪ Two recent tsunamis in late 2018, in Sulawesi and Anak Krakatau, Indonesia, where several hundred people died, were from very unusual landslide mechanisms—dual (strike-slip and landslide) and volcanic collapse—and provide new motivations for understanding these tsunami mechanisms. ▪ This is a timely, state of the art review of landslide tsunamis based on recent well-studied events and new research on older ones, which provide an important context for the recent tsunamis in Indonesia in 2018.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.253
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.017
GPT teacher head0.230
Teacher spread0.213 · 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