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Record W2557771848 · doi:10.1144/m46.54

Glacier-fed outwash plain on the Pacific margin of Canada

2016· article· en· W2557771848 on OpenAlexaffabout
J V Barrie, Kim W. Conway

Bibliographic record

VenueGeological Society London Memoirs · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsGeological Survey of CanadaNatural Resources Canada
Fundersnot available
KeywordsOutwash plainGeologyMargin (machine learning)GlacierCoastal plainGeomorphologyPhysical geographyGeographyPaleontology

Abstract

fetched live from OpenAlex

Outwash plains, sometimes known as sandar or valley trains, are broad, gently sloping, sheets of outwash sediment deposited by meltwater streams fed by glacier ablation (e.g. Church 1972; Church & Gilbert 1975; Benn & Evans 2010). They may be formed by coalescing outwash fans fed by streams emerging directly from a former ice margin or from proglacial braided rivers; such glacial meltwater streams usually have highly variable discharge and, especially when flow is high, transport large quantities of glacier-derived suspended sediment and bedload (Church & Gilbert 1975). An example of a drowned outwash plain exists off northern British Columbia in Hecate Strait (Fig. 1a), where rapid glacial retreat left an extensive plain that formerly stretched 150 km across the strait linking the British Columbia mainland to the islands of Haida Gwaii. Fig. 1. Multibeam bathymetry and cross-profile of an outwash plain that abruptly ends at a …

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 score0.015
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0010.000
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 head0.016
GPT teacher head0.204
Teacher spread0.188 · 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

Citations1
Published2016
Admission routes2
Has abstractyes

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