MétaCan
Menu
Back to cohort
Record W2387990401

The root characteristics of different alfalfa varieties

2014· article· en· W2387990401 on OpenAlexaboutno aff
Chen Cha

Bibliographic record

VenueCaoye kexue · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Productivity and Crop Improvement
Canadian institutionsnot available
Fundersnot available
KeywordsRoot (linguistics)Biomass (ecology)CollarBiologyFibrous root systemRoot systemPositive correlationAgronomyMathematicsHorticulture
DOInot available

Abstract

fetched live from OpenAlex

The root development characteristics and the correlation with the aboveground biomass of twelve alfalfa varieties introduced from American,Germany and Canada and planted in Qiannan area in Guizhou were studied.The results showed that the root morphological characteristics of different alfalfa varieties had significant difference(P0.05).The aboveground biomass had extremely significantly positive correlation(P0.01)with the root collar diameter,the branch number,the main root length,and the root dry weight.The underground biomass had extremely significantly positive correlation with the root collar diameter,the depth,the number of branches,the bud number,the main root length and the root diameter.Through path analysis,the greatest contribution factors for the root biomass were the root collar diameter,number of branches,length of main root and lateral root number.According to the root morphology characteristics,the twelve alfalfa varieties can be clustered into three categories.

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 score0.008
Threshold uncertainty score0.017

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)0.0000.000

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 head0.008
GPT teacher head0.170
Teacher spread0.162 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueCaoye kexueSame topicAgricultural Productivity and Crop ImprovementFrench-language works237,207