MétaCan
Menu
Back to cohort
Record W4311238882 · doi:10.18280/mmep.090504

Optical Parameters of the Tilia Cordata Mill. Assimilation Apparatus

2022· article· en· W4311238882 on OpenAlexvenueno aff
Rida Sultanova, М. М. Мартынова, Georgiy Odintsov, Dinar Mukhamadiev

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil and Environmental Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGrowing seasonTiliaPhenologyNormalized Difference Vegetation IndexLeaf area indexEnvironmental scienceCanopyBotanyHorticultureBiology

Abstract

fetched live from OpenAlex

Morphometric indicators of trees' assimilative apparatus, including their reflection and light-absorbing properties, largely determine their physiological processes. Leaf initiation and development depend on chlorophyll resulting from photosynthesis, water absorption, its movement through a tree and evaporation. The aim of the paper is to evaluate leaf optical properties of Tilia cordata Mill. It was found that optical coefficients of leaf blades vary depending on the time of sample collection: at the end of the growing season, the leaf blade absorptance (Ab) ranges from 68.9% to 72.4%. During the intensive formation of Tilia flowers, the Ab coefficient decreases to 59.2%. It starts to rise before the beginning of the Tilia fruit maturation. The transmittance, Tr, is also lower at the period of intense flower development. Estimating NDVI (vegetation index) and LAI (leaf area index) from Sentinel-2 satellite imagery showed that the ratio between these indices (NDVI-LAI) changes during the entire growing season. The NDVI-LAI correlation varied up to the strongest one during the entire phenological cycle.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.172
Teacher spread0.141 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueMathematical Modelling and Engineering ProblemsSame topicSoil and Environmental StudiesFrench-language works237,207