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Record W4393242186 · doi:10.54097/hbem.v21i.14425

Analysis of the Fifth Set of listing standards of China Science and Technology Innovation Board

2023· article· en· W4393242186 on OpenAlexaff
Xinyu Lu

Bibliographic record

VenueHighlights in Business Economics and Management · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Political and Economic Relations
Canadian institutionsSquamish Nation
Fundersnot available
KeywordsListing (finance)ChinaSet (abstract data type)BusinessAccountingComputer sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

With the landing of micro-electrophysiology on the Science and Technology Innovation Board, the fifth set of Science and Technology Innovation Board listing rules appeared and hoped to promote the development of new things in domestic capital production. The fifth set of Science and Technology Innovation Board listing rules reflects the inclusiveness of the Science and Technology Innovation Board because this set of listing rules is for some unprofitable or small-profit research and development technology, innovation, and future development of enterprises listed standards. Including the core technology, production products and stage results, good market trends, and innovative technological advantages. Especially for most types of biological drug development or medical technology companies. Today, almost all the companies that use the fifth set of Science and Technology Innovation Board to go public have commercialized their products, gained operating income of 100 million yuan, and some companies have even earned profits. As time goes on, the fifth set of Science and Technology Innovation Board of the development is getting better and better. There are many successful cases for other companies with the same enterprises to reference, and the future trend is also on the rise. However, due to the special characteristics of the Technology Innovation Board, the liberalization of IPO listing also brings great risks to the auditing work.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.964
Threshold uncertainty score0.263

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0000.001
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 head0.018
GPT teacher head0.278
Teacher spread0.261 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2023
Admission routes1
Has abstractyes

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