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Record W4386972764 · doi:10.5376/ijmec.2023.13.0002

The Role and Value of Ancient Trees in the Ecosystem

2023· article· en· W4386972764 on OpenAlexvenueno aff
Serein Yan

Bibliographic record

VenueInternational Journal of Molecular Ecology and Conservation · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAfrican Botany and Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiodiversityEcologyEcosystemDisciplineRoot (linguistics)Value (mathematics)Ecosystem servicesEnvironmental resource managementForest ecologyEcosystem engineerBalance of natureGeographyBiologyEnvironmental scienceComputer scienceSociologySocial science

Abstract

fetched live from OpenAlex

This study aims to explore the roles and values of ancient trees in ecosystems, providing scientific basis for the conservation and rational utilization of these trees. Through in-depth research on aspects like root systems, canopies, and ecology, this study reveals the significant roles and values of ancient trees within ecosystems. The research findings indicate that ancient trees possess well-developed root systems and dense canopies, enabling them to maintain soil fertility, enhance microenvironments, and uphold biodiversity, thereby playing crucial roles in maintaining ecological balance and preserving biodiversity. Ancient trees hold extensive and profound natural scientific value, offering essential resources and data for multiple disciplinary studies. This study emphasizes the importance of conserving ancient trees and suggests strategies for their scientific utilization. It provides scientific evidence concerning the ecological functions and values of ancient trees, offering vital insights for their conservation and informed utilization.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.095

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)0.0000.000

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 head0.011
GPT teacher head0.222
Teacher spread0.211 · 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 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

Citations5
Published2023
Admission routes1
Has abstractyes

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