MétaCan
Menu
Back to cohort
Record W7132177336

Wuling Hongguang MINIEV: A New Breed of Chinese Automaker

2022· other· W7132177336 on OpenAlexaff
Gao 王高, 朱琼

Bibliographic record

VenueCEIBS Institutional Repository · 2022
Typeother
Language
Field
Topic
Canadian institutionsCentre Casa
Fundersnot available
KeywordsBreedAutomotive industrySet (abstract data type)Selection (genetic algorithm)
DOInot available

Abstract

fetched live from OpenAlex

生存在成熟市场中的企业经常面临着两难抉择:是留在已有市场致力于打败竞争对手,还是开辟新市场,以摆脱耗费资源的既有竞争?上汽通用五菱汽车股份有限公司(简称“五菱”)选择了后者,它采取与传统造车完全不同的模式,研制出没有任何多余配置的、极简的五菱宏光MINIEV,又顺应用户需求变化与用户一起共创了潮流改装文化,逐步将宏光MINIEV打造成具有网红特质的潮创玩具,并由此摆脱了与传统汽车产品的竞争,开辟了大众潮流改装车市场。截至2021年4月底,宏光MINIEV上市9个月,连续8个月成为中国新能源车销量冠军,其中1月和4月,还蹿升至全球电动车销量翘楚之位。 不过,即使打造了这样一个炙手可热的产品,五菱的领军者,五菱总经理沈阳、副总经理薛海峰仍然面临着两难选择:宏光MINIEV的上升势头还能持续多久?未来应该制定怎样的产品战略?是沿着价格台阶向上推出升级产品,还是聚焦已有的市场推出适合的产品?

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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.041
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0040.005
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.001

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 head0.011
GPT teacher head0.246
Teacher spread0.236 · 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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueCEIBS Institutional RepositoryFrench-language works237,207