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Neoichnology of a Lake Margin in the Canadian Aspen Parkland Region, Cooking Lake, Alberta

2024· article· en· W4404167362 on OpenAlexaffabout
Ryusuke Kimitsuki, John‐Paul Zonneveld, Baptiste Coutret, Kelly Rozanitis, Yuhao Li, Kurt O. Konhauser, Murray K. Gingras

Bibliographic record

VenueSedimentologika · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMargin (machine learning)ForestryPhysical geographyHydrology (agriculture)GeographyArchaeologyGeologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Neoichnology provides insights essential for interpreting trace fossils in the rock record. Despite the wealth of studies conducted in marine nearshore environments, non-marine environments including lacustrine settings have received comparably little attention. Moreover, previous neoichnological studies of lakes are restricted to arid, semi-arid, tropical, and alkaline lakes, and there is a gap in knowledge of lakes in higher latitudes. The lake biome is controlled by multiple biotic and abiotic factors, and it is essential to compare lakes at different environmental settings to have a fuller understanding of lacustrine ichnology. Herein, we report on a trace assemblage comprising both invertebrate and vertebrate tracemakers in a natural lake situated within Canadian Aspen Parkland. Using detailed observations and photogrammetry, traces made by invertebrates such as fly larvae, beetles, and slugs, and (vertebrate) shorebirds are documented. Comparisons with current ichnofacies models show that these temperate latitude trace assemblages do not fully conform to the archetypal Mermia or Scoyenia Ichnofacies. For instance, fieldwork reveals a predominance of diminutive, penetrative burrows and simple surface trails that differ from the archetypal lacustrine ichnofacies. The study highlights the impact of environmental factors, such as water saturation and seasonal changes, on trace formation and preservation, providing insights into the ichnological characteristics of high-latitude lakes. These findings contribute to palaeoenvironmental interpretations and underscore the need for further research on the ichnology of forested lake systems, especially across different seasons and geographical settings.

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 score0.014
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.011
GPT teacher head0.221
Teacher spread0.210 · 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

Citations4
Published2024
Admission routes2
Has abstractyes

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