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Record W4406930497 · doi:10.1080/27669645.2025.2454799

Research on integrated 3D geological modeling of vector grid ——taking the core area of Tianfu New Area as an example

2025· article· en· W4406930497 on OpenAlexfundno aff
Ming Hao, Huan Liu, Bo Wang, Fang Zhou, Xianglong Zeng, Lei Yang, Deng Pan, Guojun Liao

Bibliographic record

VenueAll Earth · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Modeling and Analysis
Canadian institutionsnot available
FundersMinistry of Natural Resources
KeywordsCore (optical fiber)GridGrid cellGeologyEngineeringTelecommunications

Abstract

fetched live from OpenAlex

The development and utilisation of urban underground space is an important part of urban construction, and urban 3D geological modelling is an important standard to evaluate the difficulty of underground space development and utilisation. At present, the urban 3D geological modelling is often the construction of a single expression of the 3D model. Existing urban integration is a fusion and integration of 3D models of different spatial locations, but there is little research on the integration of different expression models in the same spatial location, especially in the integration of 3D geological structure model and 3D geological attribute model. To solve this problem, this paper takes the core business district of Tianfu New District of Chengdu city as the research area and the urban geological survey of Chengdu city as the data base, adopts the borehole-based rapid modelling technology to build the urban 3D geological structure model, uses the grid segmentation and attribute interpolation to realise the model integration, and builds the vector grid integrated 3D geological model of ‘one model, multiple expressions’. It is helpful to comprehensively consider the problems of geological structure and geological properties.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.052
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0030.000

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 head0.252
GPT teacher head0.335
Teacher spread0.083 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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