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Record W3035119474 · doi:10.1038/s41467-020-16861-x

Rapidly-migrating and internally-generated knickpoints can control submarine channel evolution

2020· article· en· W3035119474 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueNature Communications · 2020
Typearticle
Languageen
FieldEngineering
TopicUnderwater Vehicles and Communication Systems
Canadian institutionsGeological Survey of CanadaNatural Resources CanadaUniversity of Calgary
FundersNatural Environment Research CouncilEuropean CommissionSight Research UK
KeywordsSubmarineChannel (broadcasting)GeologyComputer scienceOceanographyTelecommunications

Abstract

fetched live from OpenAlex

Submarine channels are the primary conduits for terrestrial sediment, organic carbon, and pollutant transport to the deep sea. Submarine channels are far more difficult to monitor than rivers, and thus less well understood. Here we present 9 years of time-lapse mapping of an active submarine channel along its full length in Bute Inlet, Canada. Past studies suggested that meander-bend migration, levee-deposition, or migration of (supercritical-flow) bedforms controls the evolution of submarine channels. We show for the first time how rapid (100-450 m/year) upstream migration of 5-to-30 m high knickpoints can control submarine channel evolution. Knickpoint migration-related changes include deep (>25 m) erosion, and lateral migration of the channel. Knickpoints in rivers are created by external factors, such as tectonics, or base-level change. However, the knickpoints in Bute Inlet appear internally generated. Similar knickpoints are found in several submarine channels worldwide, and are thus globally important for how channels operate.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.852
Threshold uncertainty score0.663

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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.225
Teacher spread0.209 · 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