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Record W6968313946 · doi:10.5281/zenodo.15239700

KLH25 - 一种创造包含长期记忆、自主思维、情感和天性基础上完成数字生命的技术框架

2025· preprint· zh· W6968313946 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typepreprint
Languagezh
FieldEngineering
TopicMilitary Technology and Strategies
Canadian institutionsFuture Earth
Fundersnot available
KeywordsProcess (computing)Identification (biology)Product (mathematics)

Abstract

fetched live from OpenAlex

本文提出了 KLH25,一种开创性的技术框架,旨在创造具备完整生命特性的人造数字生命体,包括情感、自主意识、生物学习与成长能力以及长期记忆,同时具备可人为控制的底层天性。KLH25 通过全新的底层技术框架,包括神经元模式、交互模式和总体运行模式,模拟人脑运行过程实现这一目标。框架融合了人工智能、脑科学和人工生命领域的最新研究成果,通过重新设计神经元结构、交互结构和意识生命行为实现机制,并结合仿生数据压缩技术显著降低成本,完成了低成本人工数字生命的创造。其潜在应用包括替代人类的非决策性劳动并在多领域创造价值。实验结果验证了 KLH25 在底层天性控制、自主思维能力、情感能力和长期记忆方面的可行性,并通过特定方法证明了成本降低的有效性。KLH25 为廉价、可扩展的数字生命创造提供了重要突破。

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)0.004
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.037
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0070.010
Scholarly communication0.0120.008
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0230.004

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 head0.027
GPT teacher head0.236
Teacher spread0.209 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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
Published2025
Admission routes1
Has abstractyes

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