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Record W7086591139

Pérdidas de vidas, viviendas, infraestructura y embarcaciones por el tsunami del 27 de Febrero de 2010 en la costa central de Chile

2013· article· es· W7086591139 on OpenAlexaboutno aff

Bibliographic record

VenueScientific Electronic Library Online (Scientific Electronic Library Online) · 2013
Typearticle
Languagees
FieldEarth and Planetary Sciences
TopicGeological and Tectonic Studies in Latin America
Canadian institutionsnot available
Fundersnot available
KeywordsUrban environmentLaharNova scotia
DOInot available

Abstract

fetched live from OpenAlex

El terremoto Mw = 8.8 del 27 de febrero de 2010 en Chile se encuentra entre los sismos de mayor magnitud registrados por instrumentos a la fecha, posicionándose como el segundo más fuerte en la historia del país y uno de los diez más fuertes en el mundo registrados mediante instrumentos. Una de sus principales consecuencias fue la generación de un tsunami destructivo por la deformación del fondo marino. Las olas asolaron casi 600 km de la costa de Chile central y fueron la causa de un tercio de las víctimas fatales (181 sobre un total de 521), convirtiéndose así en el tsunami con mayor número de muertes asociadas a este tipo de eventos en Sudamérica en los últimos 30 años. En el presente trabajo se reúnen y sistematizan una serie de antecedentes entre los que se contemplan informes, artículos y campañas de investigación y evaluación post-tsunami, realizados en el litoral afectado. Se establece una caracterización cualitativa y estadística de las pérdidas de vidas humanas, viviendas, infraestructura costera y embarcaciones, separando pérdidas asociadas al tsunami de aquellas atribuibles exclusivamente al sismo. Mediante este catastro que integra información proveniente de fuentes de diferente naturaleza, se espera contribuir a evaluar los daños asociados al tsunami.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.155
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.005
Science and technology studies0.0030.005
Scholarly communication0.0050.006
Open science0.0050.001
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0540.001

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 head0.005
GPT teacher head0.214
Teacher spread0.209 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2013
Admission routes1
Has abstractyes

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