MétaCan
Menu
Back to cohort
Record W1699555701 · doi:10.1016/0967-0653(95)94265-r

10.1016/0967-0653(95)94265-r

2000· article· en· W1699555701 on OpenAlexvenueno aff
Walter J. Sexton, Maylo Murday

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoastal and Marine Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsShoreSiltGeologyTransgressiveDeltaBarrier islandSedimentRiver deltaProgradationOceanographyInletSediment transportTidal rangePlageEstuaryGeomorphologySedimentary depositional environmentStructural basin

Abstract

fetched live from OpenAlex

The shoreline of Nigeria was divided into five distinct regions based on coastal geomorphology and sedimentological parameters. During a 4-year period (1982 through 1985), 60 beach profile stations were established and monitored, covering the entire country's shoreline. Data gathered at these field stations were complemented with extensive aerial overflights conducted off the coastline during all phases of the study. The purpose of the study was to define the detailed sedimentological and morphological aspects of the Nigerian coastline from field data. The morphological regions defined along the Nigerian coast from west to east are: (1) barrier-lagoon coast, (2) transgressive mud coast, (3) delta flanks, (4) arcuate delta, and (5) strand coast. These shoreline segments exhibit distinct beach/inlet morphologies and sediment characteristics in response to their available sediment sources and to the hydrodynamic process active along each segment. Sediments on the beaches range from silt and clay (transgressive mud coast) to medium-grained sand (barrier-lagoon coast) with beach slopes ranging from 1:90 to 1:6, respectively. The coastal sediments are composed mostly of well-sorted, fine- to medium-grained, quartz-rich sand. Coastal vegetation is highly variable with over 40 different coastal plant species identified, with the greatest diversity of species occurring within the Niger Delta region.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.963
Threshold uncertainty score0.388

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)0.9990.998

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 head0.004
GPT teacher head0.146
Teacher spread0.142 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations35
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueTime to knitSame topicCoastal and Marine DynamicsFrench-language works237,207