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Record W2368097968

FEATURES, ATTRIBUTES AND RESEARCH IMPLICATIONS OF TRANSFER STRUCTURE KNOTS ALONG THE MIDDLE-LOWER YANGTZE RIVER REACHES

2010· article· en· W2368097968 on OpenAlexaff
Tu Wenchuan

Bibliographic record

VenueGeology of Anhui · 2010
Typearticle
Languageen
FieldEngineering
TopicGeoscience and Mining Technology
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsTectonicsGeologyProspectingFault (geology)Yangtze riverPaleontologyChinaMining engineeringGeography
DOInot available

Abstract

fetched live from OpenAlex

The transfer structure knots along the middle-lower Yangtze River reaches are the focal points where the Tethys tectonic mechanism meets,links up and transforms with the Pacific tectonic mechanism,substantially including the Dabie Orogen,Tan-Lu Fault and Middle-lower Yangtze metallogenic belts,referred to as three major well-known tectonic units,which are typical of deep-seated process and surface response of eastern China mid-Cenozoic continental dynamics.It will greatly favour new breakthrough in continental dynamic theory and guide deep-seated ore prospecting in second metallogenic space to combine continental orogen,large faults and mining camp,aim at intra-plate deformation,kinetics and dynamics,build up systematic research frame for continental dynamics in the area,study the delicate transformation process between two major tectonic mechanisms,and analyze the deep process and shallow effect of intra-continental tectonic evolution and dynamics..

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.258
Teacher spread0.227 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2010
Admission routes1
Has abstractyes

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