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CONIFEROUS TREES ASSOCIATED WITH INTERDUNE DEPOSITS IN THE JURASSIC NAVAJO SANDSTONE FORMATION, UTAH, USA

2007· article· en· W2143096385 on OpenAlexfundno aff
Judith Totman Parrish, Howard J. Falcon‐Lang

Bibliographic record

VenuePalaeontology · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersKillam TrustsDalhousie UniversityPalaeontological Association
KeywordsGeologyWater tablePaleontologyPluvialAeolian processesNavajoGroundwater

Abstract

fetched live from OpenAlex

Abstract: The Lower Jurassic Navajo Sandstone Formation of south‐west USA represents one of the largest erg deposits ever to have developed on Earth. Here, we report the widespread occurrence of silicified conifer stumps and trunks within interdune deposits near Moab, south‐east Utah. Where present as (par)autochthonous assemblages, trees are associated with the deposits of spring‐fed carbonate lakes. A few stumps preserved in growth position are rooted in aeolian sandstone immediately below the lake deposits, and evidently established on interdune soils in response to a rising water table. Following at least several decades of growth, trees were killed as the water table continued to rise forming shallow lakes containing ostracodes. Where present as allochthonous assemblages, randomly orientated tree trunks are associated with massive sandstone beds interpreted as fluidized mass flow deposits. These may have formed when dune slip‐faces collapsed during occasional heavy downpours of rain, destroying stands of trees. The occurrence of large conifers over a wide area of the Navajo Sandstone Formation in south‐east Utah may record long‐lived pluvial episodes during which the dune field stabilized, or reflect the erg‐margin position of the localities.

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)0.000
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 score0.122
Threshold uncertainty score0.242

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.019
GPT teacher head0.254
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

Citations49
Published2007
Admission routes1
Has abstractyes

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