Bending Strength and Porous Structure of Carbonized Panels Made from Waste Phenol-formaldehyde Resin and Magazine Paper
Bibliographic record
Abstract
リサイクルが難しいとされている廃フェノール樹脂と雑誌古紙から, フェノール樹脂接着剤を用いてパネルを形成し, さらに二酸化炭素賦活法で吸着性能を有する炭素系パネルを調製した。パネルの曲げ強度特性を調べたところ, 炭化処理で曲げ弾性率 (MOE) が増加した。ところが, 二酸化炭素賦活によりMOEと曲げ強さ (MOR) が低下した。これは, 二酸化炭素を用いた賦活処理中に, 廃フェノール樹脂中に含まれる有機物の分解がMOEやMORの低下に影響を与えたと思われる。一方, 炭素系パネルの比表面積は, 廃フェノール樹脂を含まないパネルで670～990m2/g, 廃フェノール樹脂を含むパネルでは650～760m2/gであり, 細孔構造の発達がみられた。
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".