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Record W2519241541

캐나다 오일샌드 분포지역에서의 유체기계 주행성능 평가를 위한 지반공학적 특성 분석

2016· article· ko· W2519241541 on OpenAlexaboutno aff
홍승서, 김영석

Bibliographic record

VenueThe KSFM Journal of Fluid Machinery · 2016
Typearticle
Languageko
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsnot available
Fundersnot available
KeywordsAtterberg limitsGeotechnical engineeringWater contentIndex (typography)PlasticitySpecific gravityEnvironmental scienceHydrology (agriculture)Soil scienceMaterials scienceMathematicsEngineeringComposite materialComputer science
DOInot available

Abstract

fetched live from OpenAlex

A series of laboratory tests were conducted to investigate the geotechnical engineering characteristics of muskeg soil for construction machinery widely distributed in cambridge region in Canada which makes problems in construction works. Physical characteristics of cambridge region muskeg soil were measured in terms of such categories as nature water content, organic content, specfic gravity, liquid limit, and plasticity index. As the test result, it was found that nature water content, organic content, specific gravity, liquid limit, plasticity index, and compression strength were 50.8∼343.8%, 12.1∼42.5%, 1.76∼2.57, 46.6∼440.2%, 25.6∼280.5, 0.665∼1.537 ㎏/㎠, respectively.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.198
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
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 head0.007
GPT teacher head0.202
Teacher spread0.195 · 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 teacher head, not a consensus.

Study designSimulation or modeling
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
Published2016
Admission routes1
Has abstractyes

Explore more

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