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Record W2914289608 · doi:10.9753/icce.v36.sediment.76

CHANNEL SEDIMENTATION CAUSING BY GROUPING WAVES AND WIND WAVES AT THE FISHING PORT, JAPAN

2018· article· en· W2914289608 on OpenAlexaff
Takehito Horie, Takashi Kamo, Yasuji Nozaka, Hitoshi Tanaka

Bibliographic record

VenueCoastal Engineering Proceedings · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoastal and Marine Dynamics
Canadian institutionsAlpha Technologies (Canada)
Fundersnot available
KeywordsSedimentationChannel (broadcasting)Port (circuit theory)Littoral zoneFishingLongshore driftOceanographyGeologyWind waveCurrent (fluid)BreakwaterMarine engineeringMeteorologyGeographyGeomorphologyEngineeringTelecommunicationsFisherySedimentSediment transportElectrical engineering

Abstract

fetched live from OpenAlex

Most of fishing ports in Hokkaido, Japan are located in the surf zone on the sandy beach. As a result, channel sedimentation has become a serious problem in many fishing ports. As an example, when planning a coastal structure to control littoral drift and nearshore current, annual maximum wave heights (wind waves) is used as the external forces condition in many cases. However, the effect as expected is not obtained on channel sedimentation at fishing ports in Hokkaido. To solve such a problem, it is necessary to understand the relationships between channel sedimentation and external force, and be able to reveal the developmental process of channel sedimentation. Then, field observation and theoretical approach (wave-to-wave analysis, spectral analysis, EOF analysis, et al) become important tools.

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 score0.051
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.182
Teacher spread0.175 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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