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Comment on egusphere-2024-2386

2024· peer-review· en· W4402512613 on OpenAlexaff

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGeography

Abstract

fetched live from OpenAlex

Abstract. The response of a coastal ocean model, simulating a typical Eastern Boundary system, to downwelling-favorable winds with and without the presence of a submarine canyon is studied. Three contrasting bathymetric configurations, considering shelves with different depth and slopes, are evaluated. Experiments without a submarine canyon represent the well-known downwelling circulation and cross-shore structure with a downwelling front and the development of frontal instabilities generating density anomalies in the bottom layer. The presence of the submarine canyon drives important changes in cross-shore flows, with opposing velocities on either side of the canyon. Onshore (offshore) and downward (upward) velocities develop in the upstream side of the canyon in the time-dependent and advective phases. Instabilities developed and are modified principally downstream of the canyon. Overall, the net impact of the canyon is to enhance offshore and downward transport. However, particle tracking experiments reveal that particles can become trapped inside the canyon in an anticyclonic circulation when the particles pass the canyon over the continental slope or when particles inside the canyon are affected by downwelling conditions. Overall, ~20–23 % (~15–18 %) of particles released directly upstream (in the canyon) at mid-depths become trapped inside the canyon until the end of the simulations (15 days).

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)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.623
Threshold uncertainty score0.537

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0100.005
Insufficient payload (model declined to judge)0.6230.473

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 head0.271
Teacher spread0.258 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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
Published2024
Admission routes1
Has abstractyes

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