MétaCan
Menu
Back to cohort
Record W2608202932

Effect of Microbial Induced Calcite Precipitation on Surface Erosion and Scour of Granular Soils: Proof of Concept

2017· article· en· W2608202932 on OpenAlexaboutno aff
Ruotian Bao, Junhong Li, Lin Li, Teresa J. Cutright, Long Chen, Jiahua Zhu, Junliang Tao

Bibliographic record

VenueTransportation Research Board 96th Annual MeetingTransportation Research Board · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Applications in Construction Materials
Canadian institutionsnot available
Fundersnot available
KeywordsCalciteCementation (geology)PrecipitationErosionSoil waterGeologyGeotechnical engineeringMineralogySoil scienceMaterials scienceGeomorphologyMetallurgyCement
DOInot available

Abstract

fetched live from OpenAlex

Erosion is relevant to a variety of infrastructure problems such as bridge scour, roadway shoulder erosion, coastal erosion, and riverbank and slope stability. This research investigated the feasibility of using microbial-induced calcite precipitation (MICP) as an erosion countermeasure. MICP is a natural phenomenon in which calcite precipitation occurs as a consequence of microbial metabolic activity. The precipitated calcite modifies the soil fabric and provides an additional bonding force between soil particles. In this paper, a preliminary experimental study on the erosional behavior of MICP-treated sand is presented. A standard soil, Ottawa graded sand, was treated with a bacterium (Sporosarcina pasteurii) in a full-contact reactor—one in which the soil in a fabric mold was fully immersed in the bacteria and cementation solution. The morphologies and crystalline structures of the precipitated calcite in porous sediments were characterized using microscopic imaging techniques. The treated soil samples...

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.170
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.001
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 head0.038
GPT teacher head0.368
Teacher spread0.330 · 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 designBench or experimental
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

Citations2
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueTransportation Research Board 96th Annual MeetingTransportation Research BoardSame topicMicrobial Applications in Construction MaterialsFrench-language works237,207