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Record W2134492273 · doi:10.7202/009104ar

Flood Ring Evidence and its Application to Paleoflood Hydrology of the Red River and Assiniboine River in Manitoba*

2004· article· en· W2134492273 on OpenAlexaffvenueabout
Scott St. George, Erik Nielsen

Bibliographic record

VenueGéographie physique et Quaternaire · 2004
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsManitoba HydroGeological Survey of Canada
Fundersnot available
KeywordsRiparian zoneFlood mythDendrochronologyGeologyHydrology (agriculture)Drainage basinStreamflowStructural basinForcing (mathematics)Physical geographyGeographyArchaeologyClimatologyGeomorphologyPaleontologyEcologyHabitatCartography

Abstract

fetched live from OpenAlex

Although paleoflood records developed from tree rings are much shorter than those developed from geological evidence, their brevity is offset by their exceptional utility for dating floods to a specific year. Inundation at the beginning of the growing season disturbs cambial processes in riparian Quercus spp., causing unusual anatomical features to develop within the annual ring, including small earlywood vessels, disrupted flame parenchyma and less wood fiber. These features are most strongly developed near the tree base, and may be caused by disruptions of auxin flow. Anatomical flood signatures can be used to determine the frequency, magnitude and hydrological causes of past floods, and to identify the influence of potential forcing mechanisms. In the lower Red River basin, Canada, flood-ring evidence has been used to identify several large floods during the mid 1700s, the early to mid 1800s and the latter half of the 20th century. Records for the Assiniboine River and the American portion of the Red River are developed from fewer trees, but suggest that severe floods in the Red and Assiniboine basins have coincided, albeit infrequently, during the past 500 years.

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 score0.488
Threshold uncertainty score0.989

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 head0.018
GPT teacher head0.241
Teacher spread0.223 · 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

Citations24
Published2004
Admission routes3
Has abstractyes

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