Data of "High-speed cryo-microscopy proves that ice-nucleating proteins of Pseudomonas syringae trigger freezing at hydrophobic interfaces"
Bibliographic record
Abstract
Raw data of a study titled <strong><em>"High-speed cryo-microscopy proves that ice-nucleating proteins of Pseudomonas syringae trigger freezing at hydrophobic interfaces"</em></strong>. The <strong>onset_locations.zip</strong> folder contains all analyzed images which are screenshots from the cryo-microscopic videos. Raw screenshots and evaluated images are included in two sub-folders per samples. The sample description is the name of the folders. The <strong>ice_propogation_velocity.zip</strong> folder contains all images that were used for the evaluation of the propagation velocity of ice. Every sample folder contains the original spot detection image, one image at a later time point, the subtracted image, and one image with the measured distance of the ice front indicated as white scale bar. The <strong>Results_(ice_propagation_velocity).xlsx</strong> contains the results from the velocity calculations, the <strong>Results_(surface tension).xlsx</strong> contains the evaluated surface tension values and the <strong>Results_(temperatures and locations).xlsx</strong> file contains all evaluated freezing locations (polar coordinates) and temperatures of all analyzed samples.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".