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Effects of asteroid and comet impacts on habitats for lithophytic organisms-A synthesis

2005· article· en· W1993157709 on OpenAlexaffabout
Charles S. Cockell, Pascal Lee, Paul A. Broady, D. S. S. Lim, G. R. Osinski, John Parnell, Christian Koeberl, L. J. Pesonen, Johanna Salminen

Bibliographic record

VenueMeteoritics and Planetary Science · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsCanadian Space Agency
Fundersnot available
KeywordsHabitatAsteroidEcologyCometEnvironmental scienceNicheArcticAbundance (ecology)AstrobiologyGeologyEarth scienceBiology

Abstract

fetched live from OpenAlex

Abstract— Asteroid and comet impacts can have a profound influence on the habitats available for lithophytic microorganisms. Using evidence from the Haughton impact structure, Nunavut, Canadian High Arctic, we describe the role of impacts in influencing the nature of the lithophytic ecological niche. Impact-induced increases in rock porosity and fracturing can result in the formation of cryptoendolithic habitats. In some cases and depending upon the target material, an increase in rock translucence can yield new habitats for photosynthetic cryptoendoliths. Chasmoendolithic habitats are associated with cracks and cavities connected to the surface of the rock and are commonly increased in abundance as a result of impact bulking. Chasmoendolithic habitats require less specific geological conditions than are required for cryptoendolithic habitats, and their formation is likely to be common to most impact events. Impact events are unlikely to have an influence on epilithic and hypolithic habitats except in rare cases, where, for example, the formation of impact glasses might yield new hypolithic habitats. We present a synthetic understanding of the influence of asteroid and comet impacts on the availability and characteristics of rocky habitats for microorganisms.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.046
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.000

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 head0.232
Teacher spread0.222 · 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 designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations49
Published2005
Admission routes2
Has abstractyes

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