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Record W2053290614 · doi:10.1144/0016-764903-168

Early Mississippian lycopsid forests in a delta-plain setting at Norton, near Sussex, New Brunswick, Canada

2004· article· en· W2053290614 on OpenAlexaboutno aff
Howard J. Falcon‐Lang

Bibliographic record

VenueJournal of the Geological Society · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Diversity and Evolution
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyDeltaPaleontologyPaleozoicArchaeologyPhysical geographyGeography

Abstract

fetched live from OpenAlex

Mississippian lycopsid forests in growth position are extremely rare, and their community-scale ecology remains enigmatic. This is a significant gap in our knowledge, not least because they represent the precursors of Pennsylvanian ‘Coal Forests’. In this paper, nearly 700 in situ fossil trees are described from 13 entisol or inceptisol horizons in the mid-Tournaisian Albert Formation (Horton Group) at Norton, near Sussex, New Brunswick, Canada. These trees, almost all of which are lycopsids of the Protostigmaria – Lepidodendropsis -type, are rooted mostly in the flood-disturbed interdistributary wetland deposits of prograding wave-dominated deltas. Tree mapping on extensive palaeosol surfaces indicates the existence of extremely dense forest vegetation. Scaled up to standard forestry units, densities of 10 000–30 000 trees per hectare are inferred. A significant inverse linear relationship between tree diameter and density for the five most extensive palaeosols indicates that inter-tree competition led to natural self-thinning as the forests matured. Forest maturation also led to a reduction in tree-spacing heterogeneity. Flood events regularly killed whole stands at Norton, burying trees in sandstone sheets, and preventing establishment of climax vegetation. Charcoal remains demonstrate that wildfire was another important disturbance process.

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 score0.473
Threshold uncertainty score0.592

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 studies0.0000.000
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 head0.011
GPT teacher head0.180
Teacher spread0.169 · 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

Citations25
Published2004
Admission routes1
Has abstractyes

Explore more

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