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Record W2282733653 · doi:10.6000/1927-5129.2016.12.08

Combining Ability Estimates for Yield and Fiber Quality Parameters in Gossypium Hirsutum L. Hybrids

2016· article· en· W2282733653 on OpenAlexvenueno aff
Mah-e-Jabeen Memon, Moula Bux Kumbhar, Muhammad Jurial Rind, Mohammad Ibrahim Keerio, Shabana Memon

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicResearch in Cotton Cultivation
Canadian institutionsnot available
Fundersnot available
KeywordsDiallel crossHybridBiologyGossypium hirsutumHorticultureCultivarInheritance (genetic algorithm)Genetic diversityBiotechnologyGeneticsBotanyGeneMedicine

Abstract

fetched live from OpenAlex

General and specific combining ability effects were discriminated in different parents and offspring to isolate the potential of genotypes used in diallel system to attain the genetic inheritance pattern ascertain with the nature of gene action. A six-by-six, hirsutum diallel excluding reciprocals, was analyzed for general and specific combining ability estimates and components of genetic variation to investigate the genetic retrospect and inheritance pattern of eleven quantitative and fiber quality characters. Hirsutum cultivars included CIM-506, BH-160, NIAB-111, CIM-497, NIAB-999 and RH-510. Some of the traits like boll number, boll weight and sympodia plant-1 did not reveal the highest GCA scoring parent for seed cotton yield. The ranking order for GCAs of the parents was not maintained from F1 to F2diallel set and the ranking order of the hybrids with respect to their SCA values was also not maintainable from F1 to F2 diallel set. Thus the hybrids could not maintain their superiority (or inferiority) of their SCA values.

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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.106
GPT teacher head0.333
Teacher spread0.227 · 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

Citations7
Published2016
Admission routes1
Has abstractyes

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