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Record W4248252818 · doi:10.1002/9781118451410.ch2

Geological Framework of Large Rivers

2020· other· en· W4248252818 on OpenAlexaff
Avijit Gupta, Olav Slaymaker, Wolfgang J. Junk

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEarth and Planetary Sciences
TopicGeological formations and processes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTectonicsGeologyLithologyDrainage basinStructural basinGeologic mapSedimentPrecipitationScale (ratio)GeomorphologyEarth scienceHydrology (agriculture)PaleontologyGeographyGeotechnical engineeringCartography

Abstract

fetched live from OpenAlex

The geological framework of a large river is formed primarily by past large-scale tectonics. Its basin should also be big enough to collect sufficient precipitation to form and support a major river system. The physical characteristics of a large river depend on its structural framework, its geological history, and its pattern of water and sediment supply. Such characteristics form and maintain the river and its basin. An uplifted zone, often formed by plate collisions, and an adjoining uplifted sub-continental-scale catchment area, are the necessary requirements for a major river. Large rivers differ in their form and function, and for many rivers the understanding of such differences is achieved via a history of continental plate tectonics and lesser tectonic movements. Geological structure and lithology tend to control the basic characteristics of the rivers. The morphology and behaviour of a large river reflect structural control at several levels.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.048
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.001

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 head0.014
GPT teacher head0.221
Teacher spread0.207 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations0
Published2020
Admission routes1
Has abstractyes

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