{
  "abstract": "This monograph formalizes the author's strategic paradigm shift from generating 3,000 stochastic AI videos (2023–2024, using spatiotemporal pixel/patch diffusion models such as Sora) to authoring 3,000 deterministic mathematical-scientific monographs and structured musical works (2025–2026) from the perspectives of Algorithmic Information Theory (Kolmogorov complexity), Philosophy of Science (Popperian pinpoint falsifiability), and Computer Science.\n\nWhile a single AI-generated video requires C_storage(V) approx. 10^8 to 10^9 bytes of high-entropy pixel tensors (hundreds of GB to terabytes for 3,000 videos), it suffers from a fatal Non-Local Black-Box Debugging Failure: as demonstrated by empirical anatomical hallucinations in Sora where a human or animal suddenly sprouts a third leg (「SORAは足が3本出たりしました」), continuous score-matching diffusion lacks a symbolic skeletal graph invariant (deg(v_pelvis) = 2) and exhibits dense Jacobian coupling (d x_0 / d c_prompt != 0), making it impossible to locally correct the third leg without re-sampling the entire stochastic video trajectory.\n\nConversely, symbolic representations—LaTeX mathematical equations, formal propositions, and musical scores/lyrics—compress storage by 10^3 to 10^4x (approx. 10^5 bytes/artifact, fitting all 3,000 monographs onto a single microSD card) while enabling Orthogonal Pinpoint Debugging (d m_j / d m_k = 0 for j != k). We further prove this principle in generative music AI: whereas kanji lyrics exhibit positive Grapheme-to-Phoneme (G2P) conditional Shannon entropy H(P_mora | C_kanji) > 0 causing misreadings, the author's empirical engineering workaround of converting misread kanji words into hiragana (「音楽生成は漢字読むのが苦手なのでひらがなで書いたり工夫しています」) acts as an injective zero-entropy phonetic projection H(P_mora | Phi_hiragana(C_kanji)) = 0 bits with zero side-effect on the musical structure (d Melody(t) / d Phi_hiragana(w_k) = 0). Finally, we formalize how this symbolic transition anchors Human-in-Command (HIC) 30-minute interactive peer review, 64-bit Goldilocks QFS-zkVM verification, and Strict No-Learn Covenant (NLL-v1.0-2026) sovereign IP protection.\n\n【和文要旨:確率的ピクセル拡散から決定論的シンボリック論文への転換——3,000件の生成アーカイブにおける情報理論的圧縮、ピンポイント反証可能性、Soraの「3本足」位相破綻と音楽AIの「ひらがな音韻確定」に見る決定論的デバッグ、および主権的知財監査】\n\n本モノグラフは、2023〜2024年における3,000本の確率的動画生成(Sora等の時空間拡散モデル)の実践から、2025〜2026年における3,000本の決定論的・数理科学モノグラフおよび構造化音楽生成への戦略的転換を、情報理論(コルモゴロフ複雑性・エントロピー圧縮)・科学哲学(ピンポイント反証可能性)・計算機科学の観点から数理定式化するものである。\n\n動画データは1本あたり 10^8〜10^9 bytes の高エントロピーなピクセル配列を要するにもかかわらず、物理法則や解剖学的位相の局所的な破綻——代表例としてSoraにおいて人物や動物の「足が3本出現する」現象——に対して「どの変数・どの式が誤っているか」を記号的に特定・局所修正(デバッグ)できないという構造的欠陥(非局所的ブラックボックス問題)を抱えている。\n\n対照的に、LaTeX数式・論理命題・音楽スコア・音韻記号等のシンボリック表現は、データ容量を約 1/1,000〜1/10,000(数百KB、3,000本すべてがmicroSDカード1枚に完全格納可能)へ劇的に圧縮しながら、1文字・1係数・1モーラ単位でのピンポイントな誤り検出(間違い探し)と決定論的修正を可能にする。その実践的証明として、音楽生成AIが漢字の多義的な読み(高い書記素・音素条件付きエントロピー H(P | C_kanji) > 0)で誤読を起こす問題に対し、歌詞をあえて「ひらがな」で記述する工夫が、条件付きエントロピーをゼロ(H(P | C_hiragana) = 0)にする決定論的記号射影として機能することを示す。本稿は、この「確率的ピクセル空間」から「決定論的シンボリック空間」への移行が、Human-in-Command(HIC)による厳密な査読、QFS-zkVM検証、およびNLL-v1.0-2026に基づく主権的知財保護の不可欠な基盤であることを証明する。\n\nLicense & Integrity Covenant: Creative Commons Attribution 4.0 International (CC BY 4.0) with Strict No-Learn Covenant (NLL-v1.0-2026).",
  "abstract_shown": true,
  "affiliations": [
    "Autonomous Living & Physical Infrastructure Institute, Iwakuni, Yamaguchi, Japan"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 1,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Yoko(洋子) Hasebe(長谷部)"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/2yse98zd79dh9.bib",
  "cited_by": 0,
  "doi": "10.5281/zenodo.23457431",
  "fulltext_url": null,
  "id": "2yse98zd79dh9",
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  "landing_url": "https://zenodo.org/records/23457431",
  "language": "eng",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [],
  "openalex": null,
  "pdf_url": "https://zenodo.org/api/records/23457431/files/stochastic_video_to_deterministic_symbolic_monographs_qfs.pdf/content",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-18",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/2yse98zd79dh9.ris",
  "sources": [
    {
      "first_seen": "2026-11-01T12:20:57Z",
      "native_id": "23457431",
      "source": "zenodo",
      "url": "https://zenodo.org/records/23457431"
    }
  ],
  "subjects": [],
  "title": "From Stochastic Pixel Diffusion to Deterministic Symbolic Monographs: Information-Theoretic Compression, Pinpoint Falsifiability, Topological Invariance vs. Three-Legged Hallucinations in Sora, Hiragana Phonetic Disambiguation in Music AI, and Sovereign IP Auditing across 3,000 AI-Generated Artifacts",
  "title_text": "From Stochastic Pixel Diffusion to Deterministic Symbolic Monographs: Information-Theoretic Compression, Pinpoint Falsifiability, Topological Invariance vs. Three-Legged Hallucinations in Sora, Hiragana Phonetic Disambiguation in Music AI, and Sovereign IP Auditing across 3,000 AI-Generated Artifacts",
  "type": "preprint",
  "updated_at": "2026-11-01T12:20:57Z",
  "url": "https://research.draconitic.com/paper/2yse98zd79dh9",
  "venue": "Zenodo",
  "versions": []
}