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Record W7132454969

Zhiyuanhui's Digital Innovation: Technology First or Scenario First?

陈桓亘, 廖毅, 赵丽缦, 何为, 李晓天, Guo 白果

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCEIBS Institutional Repository · 2024
Typeother
Language
Field
Topic
Canadian institutionsCentre Casa
Fundersnot available
KeywordsProcess (computing)Key (lock)Work (physics)Set (abstract data type)Focus (optics)
DOInot available

Abstract

fetched live from OpenAlex

本案例详细阐述了成都智元汇信息技术股份有限公司(简称“智元汇”)自2010年成立以来在公共交通领域的数字创新探索。成立伊始,智元汇便坚定地采用了“数字技术+场景运营”双管齐下的策略。随后,通过将数字技术与实际应用场景相结合并持续优化迭代,智元汇相继推出了多款全球首创的创新产品,如“智汇屏”,“二维码乘车”,“刷脸乘车”,以及“戴口罩刷脸乘车”等,在地铁等应用场景中构建了一个持续优化升级的“智慧乘运管理服务体系”。2020年,智元汇进入“智慧城市”建设领域,取得一些成绩,但也面临着新的市场环境和竞争挑战。2022年2月,邓波需要重新审视智元汇一贯坚守的发展策略:在智慧城市领域,如何完善其在“智慧交通”领域的“数字技术+场景运营”的平衡发展模式?“数字技术”和“场景运营”的战略优先级如何选择?

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.326
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0080.012
Science and technology studies0.0030.009
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0070.157

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 head0.019
GPT teacher head0.252
Teacher spread0.233 · 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

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueCEIBS Institutional RepositoryFrench-language works237,207