P-12 Potential Compact Fiberboard From Combining Shredded Corrugated Cardboard and PET Water Bottles
Bibliographic record
Abstract
Corrugated cardboard and plastic bottles (PET) can each be recycled; however the current research is looking at recycling both cardboard and PET into a new combined material. The current method of recycling corrugated cardboard is to shred and recombine the material to make new cardboard. According to the Container Recycling Institute (http://www.container-recycling.org/), only 7.5% of PET manufactured in the US and Canada are recycled. The sheer amount of corrugated cardboard and PET bottles can be recycled for other practical uses. Corrugated cardboard and PET bottles, when shredded and placed into a 3x3x6 inch mold, can be combined together and baked in an oven under compression. The shredded PET bottles will act as the combining agent to hold the shredded cardboard in the shape of a compact fiberboard.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".