Dual-axis video observations of ice crushing utilizing high-speed video for one perspective
Bibliographic record
Abstract
Rectangular thick sections (1 cm thickness) of lab-grown monocrystalline ice have been confined between two thick Plexiglas plates and crushed at -10º C from one edge face at a rate of 1 cm/s using a transparent Plexiglas platen (1 cm thickness) inserted between the plates. The transparent plates and platen permitted side viewing of the ice behavior during crushing using high-speed video and also a top view of the ice/platen contact zone through the crushing platen using regular video. Zones of intact ice at the ice/platen interface were evident in the visual records and these were shaped by cracks and spalls. The production and flow of liquid in a thin layer at the intact ice/platen interface was also evident. A novel method was used to obtain pressure measurements at the ice/platen interface. Pressure values for the intact ice contact zones were high (at least 20 MPa) and for the crushed ice the pressure varied from low (~1 MPa) to high values (~20 MPa) depending on its thickness over intact ice. Also, wetting from liquid produced at the intact ice/ platen interface probably softened and reduced the pressure in pulverized ice. Features of the load and pressure data are discussed in the context of the visual observations.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".