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Record W2943259426 · doi:10.5539/jas.v11n6p247

Crown Efficiency and Pine Cones Production for Brazilian Pine (Araucaria angustifolia (Bertol.) Kuntze) in South Brazil

2019· article· en· W2943259426 on OpenAlexvenueno aff
André Felipe Hess, Kemely Alves Atanazio, Geedre Adriano Borsoi, Luís Paulo Baldissera Schorr, Isadora de Arruda Souza, Emanuel Arnoni Costa, Danieli Regina Klein, Sandra Mara Krefta, Thiago Floriani Stepka, Roberta Abatti, Polliny Ricken, Gabriel Teixeira da Rosa

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsnot available
FundersUniversidade do Estado de Santa CatarinaFundação de Amparo à Pesquisa e Inovação do Estado de Santa Catarina
KeywordsAraucariaCrown (dentistry)ForestryDiameter at breast heightMathematicsCanopyBotanyTree (set theory)BiologyHorticultureGeography

Abstract

fetched live from OpenAlex

Crown efficiency is a relation of growth with the area tree occupies (available area efficiency). Efficiency is associated with the vertical and lateral expansion capacity of the tree and crown, increase, density and light absorption. Thus, our study aimed to evaluate crown efficiency with pine cones∙tree-1 production and dendro/morphometric variables of individual araucaria trees in three forest sites in south Brazil. In each site of each tree, dendrometric and morphometric variables were measured and increment rolls were taken at the breast height diameter level. Together with these data, the morphometric indexes, annual periodic increment in diameter of the last ten years (APId) and efficiency of the crown as a function of APId by the horizontal projection area of the crown (hpac) and number of pine cones∙tree-1 (np) by hpac were calculated. Crown efficiency was modeled as a function of the independent variables hpac, APId, crown length (cl), crown ratio (cr) and np. The accuracy of the adjustment was evaluated by the statistics of the deviance, Akaike’s information criterion and graph of the residuals. The results show that the number of pine cones∙tree-1 increases with annual periodic increment in diameter and diameter. Crown efficiency decreases with increasing hpac, cl and cr, indicating silvicultural treatments should be performed with the removal of trees of larger diameter and crown size. A higher pine cones production and efficiency correlates with forest growth, shape, competition, sociological position (stratum tree occupies) and density.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.005
GPT teacher head0.217
Teacher spread0.213 · 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

Citations9
Published2019
Admission routes1
Has abstractyes

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