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Record W3087700534

Transient and Disruption Cavity Dimensions of Complex Terrestrial Impact Structures Derived from Magnetic Data

2003· article· en· W3087700534 on OpenAlexaff
Mark Pilkington, A. R. Hildebrand

Bibliographic record

VenueLunar and Planetary Science Conference · 2003
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of CalgaryGeological Survey of Canada
Fundersnot available
KeywordsImpact craterGeologyTransient (computer programming)Magnetic anomalyAnomaly (physics)GeophysicsPhysicsCondensed matter physics
DOInot available

Abstract

fetched live from OpenAlex

[1] Accurate transient and disruption cavity dimensions are critical for estimating the energy release associated with impact. Transient and disruption cavity size can, in principle, be inferred from morphometric relationships based on crater diameter. However, locating the crater rim can be difficult for eroded terrestrial craters, and existing morphometric relationships are mostly based on observations of extraterrestrial craters where morphologic features at best provide imprecise constraints on the collapsed disruption cavity margin. Fortunately, magnetic survey data collected over terrestrial impact structures demonstrate that collapsed disruption cavity size can be estimated directly from changes in the magnetic anomaly character. A lower bound on this parameter can be defined by the outer limit of short-wavelength, intense magnetic anomalies produced by impact melt and/or suevite deposits. An upper bound is given by the inner limit of magnetic anomaly trends associated with the pre-impact target rock configuration. Using published values of crater diameters (D) and values of collapsed disruption cavity diameters (DCDC) derived from magnetic data for 19 complex terrestrial impact structures, we derive the relationship DCDC = 0.49D. These data and the possibility of geometrical similarity in crater collapse suggest that this relationship is independent of complex crater size over more than a decade of size variation.

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 score0.294
Threshold uncertainty score0.409

Codex and Gemma teacher scores by category

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

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 head0.058
GPT teacher head0.279
Teacher spread0.221 · 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
Published2003
Admission routes1
Has abstractyes

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