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Record W2148831745 · doi:10.1111/gfl.12059

Fractal analysis of veins in <scp>P</scp>ermian carbonate rocks in the <scp>L</scp>ingtanchang anticline, western <scp>C</scp>hina

2013· article· en· W2148831745 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGeofluids · 2013
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsGeological Survey of CanadaDalhousie University
FundersNational Key Research and Development Program of ChinaChengdu University of Technology
KeywordsPower lawDistribution (mathematics)FractalGeologyAnticlineVeinExponential functionGeometryStructural basinMineralogyGeomorphologyMathematicsMathematical analysisStatisticsInternal medicine

Abstract

fetched live from OpenAlex

Abstract Statistical analysis of the thickness distribution of veins in the Lingtanchang structure, southern Sichuan basin, western China, indicates that vein thickness conforms to fractal character and a power‐law distribution, whereas various distributions of veins are indicated by both the spacing distribution and the C v values. According to geometry and structure, the veins in the Lingtanchang structure can be divided into confined and through‐going veins. The statistical analyses show that confined intralayer veins are consistent with a power‐law distribution in thickness, with D t values of 1.1–1.7 and a log‐normal distribution in spacing with C v values of 0.8–0.9. The confined intra‐ to interlayer veins show D t values of 1.0–1.3 and an exponential distribution in spacing, with C v values of 0.9–1.0, indicating an unconnected vein network with weak ability for paleofluid flow. However, the through‐going veins show the lowest D t values of 0.6–0.8 with a power‐law distribution in thickness and power‐law to exponential distribution in spacing with C v values of 1.5–3.2. Differences in spacing distribution and in the thickness of veins can be explained by different stages of vein growth from confined to through‐going veins. Such processes are dominant with percolating cluster models, which significantly controls spatial distribution of veins and paleofluid flow, and therefore the reservoir conditions in the southern Sichuan basin.

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.

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)0.001
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 score0.246
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0000.000
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 head0.010
GPT teacher head0.226
Teacher spread0.215 · 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