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Record W4233415357 · doi:10.1144/sp488

About this title - River to Reservoir: Geoscience to Engineering

2019· article· en· W4233415357 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueGeological Society London Special Publications · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater and Watershed Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsEarth scienceGeologyHydrology (agriculture)Geotechnical engineering

Abstract

fetched live from OpenAlex

This volume brings together a number of papers from two workshops with the theme, ‘Rain, Rivers, Reservoirs’, which considered the dynamic changes to river systems as part of natural processes, particularly changing climatic conditions. Bringing researchers from two different locations to Brazil and the UK allowed scientists to contribute to and promote, ‘debate on current research…on how the planet works and how we can live sustainably on it’. This volume features a series of papers on the geoscience of modern and ancient rivers from across the world (Brazil, United States, Spain, Argentina, Canada, India and the UK), their evolution through time, their management, their deposits and their engineering, with both subsurface aquifers/hydrocarbon reservoirs (of Carboniferous, Triassic and Cretaceous age) and surface reservoirs considered.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.964

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0390.037

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 head0.010
GPT teacher head0.216
Teacher spread0.206 · 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