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Record W2985722939 · doi:10.7554/elife.34286.047

Author response: Novel transgenic pigs with enhanced growth and reduced environmental impact

2018· peer-review· en· W2985722939 on OpenAlexaff
Xianwei Zhang, Zicong Li, Huaqiang Yang, Dewu Liu, Gengyuan Cai, Guoling Li, Jianxin Mo, Dehua Wang, Cuili Zhong, Haoqiang Wang, Yue Sun, Junsong Shi, Enqin Zheng, Fanming Meng, Mao Zhang, Xiaoyan He, Rong Zhou, Jian Zhang, Miaorong Huang, Ran Zhang, Ning Li, Mingzhe Fan, Jinzeng Yang, Zhenfang Wu

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Genetics and Reproduction
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPhytaseDigestion (alchemy)PhosphorusTransgeneNutrientStarchNitrogenBiologyBiotechnologyFood scienceEnzymeAnimal scienceChemistryBiochemistryGeneEcology

Abstract

fetched live from OpenAlex

Transgenic expression of glucanase, xylanase and phytase in pigs enhances growth performance and reduces nitrogen/phosphorus emission, and offers a very valuable biological strategy for sustainable resource utilization and environmental protection in the pork industry.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.112
Threshold uncertainty score0.375

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.1120.031

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 head0.017
GPT teacher head0.295
Teacher spread0.277 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2018
Admission routes1
Has abstractyes

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