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A meteorite crater on Earth formed on September 15, 2007: The Carancas hypervelocity impact

2009· article· en· W2132153527 on OpenAlexaff
G. Tancredi, J. Ishitsuka, P. H. Schultz, R. Scott Harris, Peter Brown, D. O. Revelle, K. Antier, Alexis Le Pichon, Domingo Rosales, Erick Vidal, M. E. Varela, J. Bojorquez, Denis P. Cabezas, A. Dalmau

Bibliographic record

VenueMeteoritics and Planetary Science · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsWestern University
Fundersnot available
KeywordsImpact craterHypervelocityMeteoriteGeologyMeteoroidAstrobiologyEvent (particle physics)Fragmentation (computing)AstronomyPhysicsAstrophysics

Abstract

fetched live from OpenAlex

Abstract— On September 15, 2007, a bright fireball was observed and a big explosion was heard by many inhabitants near the southern shore of Lake Titicaca. In the community of Carancas (Peru), a 13.5 m crater and several fragments of a stony meteorite were found close to the site of the impact. The Carancas event is the first impact crater whose formation was directly observed by several witnesses as well as the first unambiguous seismic recording of a crater‐forming meteorite impact on Earth. We present several lines of evidence that suggest that the Carancas crater was a hypervelocity impact. An event like this should have not occurred according to the accepted picture of stony meteoroids ablating in the Earth's atmosphere, therefore it challenges our present models of entry dynamics. We discuss alternatives to explain this particular event. This emphasizes the weakness in the pervasive use of “average” parameters (such as tensile strength, fragmentation behavior and ablation behavior) in current modeling efforts. This underscores the need to examine a full range of possible values for these parameters when drawing general conclusions from models about impact processes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.074
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.245
Teacher spread0.235 · 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 source (direct Gemma or distilled Codex), 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

Citations65
Published2009
Admission routes1
Has abstractyes

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