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Record W2096613958 · doi:10.1130/g34319y.1

Global (latitudinal) variation in submarine channel sinuosity: REPLY

2013· article· en· W2096613958 on OpenAlexaff
Jeff Peakall, Mathew G. Wells, Remo Cossu, Ian Kane, D.G. Masson, Gareth M. Keevil, William D. McCaffrey, Ransome Corney

Bibliographic record

VenueGeology · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological formations and processes
Canadian institutionsUniversity of Toronto
FundersNatural Environment Research CouncilSight Research UK
KeywordsSinuosityGeologySubmarineChannel (broadcasting)LatitudeSedimentVariation (astronomy)GeomorphologyOceanographyGeodesy

Abstract

fetched live from OpenAlex

We thank Sylvester et al. (2013) for the opportunity to further consider the nature of, and controls on, sinuosity variation in submarine channels. However, in stating that we propose a Coriolis force (Fc) control on the correlation between peak sinuosity and latitude, and discounted slope and sediment supply, Sylvester et al. misquote us. We concluded “The most probable causative controls on [the] global distribution [of peak sinuosity with latitude] are the Coriolis force… and latitudinal variations in both the nature of flows and sediment type” (Peakall et al., 2012, p. 14). Slope was shown to be a very weak control on global channel sinuosity variation, though it is important in controlling sinuosity in individual channels (Peakall et al., 2012, our figures 1 and 2A).

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score1.000

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)0.0070.001

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 head0.013
GPT teacher head0.203
Teacher spread0.190 · 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; both teacher heads agree on what is shown here.

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

Citations46
Published2013
Admission routes1
Has abstractyes

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