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Record W2351047608

Selection Experiment and Analysis of Nursery Substrate in Transplanting the Tissue Culture Seedlings of Tectona grandis

2013· article· en· W2351047608 on OpenAlexvenueno aff
Bai Ling-ha

Bibliographic record

VenueSeed · 2013
Typearticle
Languageen
FieldEngineering
TopicCivil and Geotechnical Engineering Research
Canadian institutionsnot available
Fundersnot available
KeywordsCunninghamiaSawdustSeedlingTectonaTopsoilBark (sound)HorticultureTransplantingCarbonizationBotanyBiologyChemistryEcologySoil water
DOInot available

Abstract

fetched live from OpenAlex

We carried out some experiments on different nursery substrates,e. g. carbonized bark,sawdust,carbonized sawdust,topsoil of Cunninghamia lanceolata,with 12 different treatments during transplanted the tissue culture seedlings of Tectona grandis. Results shows that( 1) sawdust and topsoil of Cunninghamia lanceolata can promote survival rate of the seedlings;( 2) sawdust is the only substrate that promotes the preserving rate;( 3) carbonized bark and topsoil of Cunninghamia lanceolata can accelerate the growth of seedling height and diameter;( 4) the survival rate and the preserving rate of seedling in the treatment of 50%carbonized bark + 50% topsoil of Cunninghamia lanceolata and the treatment of 80% carbonized bark + 10%carbonized sawdust + 10% sawdust are greater than 95. 1% and 95. 0%,and the average height and average diameter of one-year-seedlings in the above treatments reach 33. 4 cm,0. 68 cm respectively.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

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 integrity0.0000.001
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 head0.221
Teacher spread0.216 · 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 designBench or experimental
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

Citations0
Published2013
Admission routes1
Has abstractyes

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