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Record W2783141678 · doi:10.1017/s108933260000070x

The Paleosol Record of Increasing Plant Diversity and Depth of Rooting and Changes in Atmospheric pCO<sub>2</sub> in the Siluro-Devonian

2000· article· en· W2783141678 on OpenAlexaboutno aff
Steven G. Driese, Claudia I. Mora, Jennifer M. Elick

Bibliographic record

VenueThe Paleontological Society Papers · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Diversity and Evolution
Canadian institutionsnot available
Fundersnot available
KeywordsPaleosolGeologyPaleontologyTerrestrial ecosystemTerrestrial plantDevonianPedogenesisTerrigenous sedimentEcosystemEarth scienceArchaeologySedimentary rockEcologyGeographySoil waterSoil scienceBiologyLoess

Abstract

fetched live from OpenAlex

Paleosols Crop Out extensively in the Appalachian region of eastern North America, from the Canadian Maritime Provinces southward to the Tennessee-Alabama border along the western side of the Appalachian Orogen (Fig. 1). The paleosols occur primarily in terrigenous clastic redbed deposits ranging in age from Late Ordovician to Early Permian (Mora and Driese, 1999; Driese and Mora, in press ), which encompass a time interval characterized by rapid evolution and diversification of terrestrial ecosystems (Table 1). These Appalachian paleosols formed under relatively constant sediment-source area and pedogenic environments (Table 1); thus they share generally uniform physical and chemical properties. As such, they are suitable particularly for investigating evolutionary advances in the gross morphology of plant roots and rhizomes, preserved as traces, and their relationship to physical and chemical features in the paleosols (Table 2). Important changes in plant abundance, rhizome and root systems, and adaptive capabilities are recorded in the paleosols, concurrent with a proxy record of changing environmental conditions. Paleosols represent a still-underutilized record of the terrestrial ecosystem (Retallack, 1990).

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)0.001
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 score0.069
Threshold uncertainty score0.955

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.016
GPT teacher head0.176
Teacher spread0.160 · 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

Citations15
Published2000
Admission routes1
Has abstractyes

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