Bibliographic record
Abstract
１．はじめに / ２． コンテナ用クレーン製造で市場をリードするキュンツ（有）（Künz GmbH） / ３． 地元大企業からのスピンアウト：ツェット‒ヴェルクツォイクバウ（ 有）（ z-werkzeugbaugmbh） / ４． EU 市場で存続戦略を推進する小規模製粉企業：フォラールベルガー・メール（Vorarlberger Mehl: Vorarlberger Mühlen und Mischfutterwerke GmbH） / ５． 地元ニーズに応えかつ移出を推進するフォラールベルクミルヒ協同組合（ Vorarlberg Milch eGen） / ６． 特製ベッドの開発製造で躍進した職人企業：“ ディー・コーイェ”・クリスティアン・ライディンガー（有）（“Die Køje”Christian Leidinger GmbH） / ７．「 スタートアップのくに（Start-up Land）」を目指す政策 / ８．おわりに / 注 / 文献 / 英文要旨
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.012 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".