Bibliographic record
Abstract
This paper explains clearly the conception of timbre, and analyses theoretically the reasons why the timbre of piano changes. By closely connected with teaching work, the author corrects some errors in the application of timbre and offers some good advice in mastering this concept in teaching. Key words： Frequency, ground note, harmonic, compound tone, timbre Resume: Ce texte explique la definitin de timbre dans un langue simple et claire , et ensuite analyse , sur le plan theorique , la raison pour laquelle le timbre du piano varie . Etroitement lie a la pratique de l’enseignement , ce texte redresse quelques erreurs de la conception du timbre dans l’application , tout en donnant des conseils utiles pour bien la maitriser dans l’enseignement . Mots-cles: frequence , ton fondamental , harmonique , ton compose , timbre 摘要：文章圍繞音色的定義周密地進行了深入淺出地解讀，進而從理論上分析了鋼琴音色產生變化的原因。文章密切聯繫教學實際，糾正了在音色概念應用上出現的一些偏差，並針對教學中應如何把握這一概念提出了一些有益的建議。 關鍵詞：頻率；基音；泛音；複合音；音色
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".