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Record W4214809305 · doi:10.1155/2022/9243361

Experimental Investigation Monitoring the Saturated Line of Slope Based on Distributed Optical Fiber Temperature System

2022· article· en· W4214809305 on OpenAlexfundno aff
Feng Li, Qin Weixing, HU Hui-ren

Bibliographic record

VenueAdvances in Materials Science and Engineering · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
FundersHunan Provincial Innovation Foundation for PostgraduatePetroleum Technology Research CentreNational Natural Science Foundation of China
KeywordsMaterials scienceRepeatabilityLine (geometry)FiberOptical fiberTemperature measurementComposite materialAnalytical Chemistry (journal)OpticsThermodynamicsChromatography

Abstract

fetched live from OpenAlex

The position of the saturated line is an important basis for evaluating the stability of the slope, and the traditional sensors cannot be monitored for a long time because of poor durability and anti-interference. A method for measuring the saturated line with distributed optical fiber temperature measurement technology was proposed, and the one-dimensional and two-dimensional model experiments of measuring the saturated line at three kinds of electron flow (5 A, 10 A, and 15 A) were conducted, and their measuring data were carefully analyzed. The results showed the three stages of the optical fiber temperature difference with time: sudden-rising, fast-rising, and slow-rising. The temperature rising rate and stable temperature difference at the position of the saturated line are between saturated soil and unsaturated soil. The fiber optic temperature increases with the increment of heating electron flow, which also demonstrates stability and repeatability.

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 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 score0.682
Threshold uncertainty score0.217

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.212
Teacher spread0.202 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations6
Published2022
Admission routes1
Has abstractyes

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