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Record W2991690121 · doi:10.1139/er-2019-0045

Generated land systems: recognition and prospects of land system science

2019· article· en· W2991690121 on OpenAlexvenueno aff
Li Fei, Zhou Meijun, Zhangxuan Qin

Bibliographic record

VenueEnvironmental Reviews · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsAdaptabilityEnvironmental resource managementLand useLand managementEarth system scienceLand degradationComputer scienceLand information systemPsychological resilienceSystems scienceEnvironmental planningEnvironmental scienceEcologyCivil engineeringEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Although land system research has made important progress in land change monitoring, long-term histories of land use change, land system change modeling, and case-study synthesis, it still faces some challenges in system integration and comprehensive analysis. To better understand and explore the comprehensiveness of land systems, system integration theory should be combined with system generation theory that emphasizes historical accumulation. Therefore, this paper revisits some of the basic connotations and theories of land system science by reviewing relevant research and proposes the concept of generated land systems based on system generation theory with an aim to providing a reference base for future research. As coupled human–environment systems are generated by mankind’s transformation, utilization, and adaptation of the land surface and its upper and lower spaces of Earth, generated land systems evolve in the mutual generation and restriction of the biophysical environment, land use, and social economy. The evolution forms of generated land systems can be classified as fluctuation, degradation, and optimization based on the ascendency and resilience of the system. The need for generated land systems to be multi-functional is what motivates the direction and form of generated land system evolution. Generation mechanism, process, adaptability, scale effect, and tele-coupling are important issues of generated land system research. In addition, how generated land systems can enter a new evolutionary cycle through functional transformation is also crucial to achieving sustainable management and utilization of land resources.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.003

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 head0.016
GPT teacher head0.203
Teacher spread0.187 · 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 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

Citations11
Published2019
Admission routes1
Has abstractyes

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