Bibliographic record
Abstract
Thermal conductivity kappa of seven polymerizing liquids has been measured in real time at different temperatures, and calorimetry and dielectric spectroscopy of one liquid are performed to help interpret the results. As a covalently bonded linear chain or a network structure in the liquid grows, kappa of the Debye equation initially increases with the polymerization time t(polym) as the molecular weight, density, and sound velocity increase, as on cooling a liquid. The measured kappa reaches a maximum and then decreases, thus showing a peak at a certain t(polym) and finally becomes constant, which is not the true behavior of steady state kappa. The dielectric relaxation time of the covalently bonded structure at the t(polym) for the kappa peak is less than 5 s and the extent of polymerization is below the vitrification plateau value. The peak height increases when the pulse time for kappa measurement is increased. An increase in the liquid's temperature shifts the kappa peak to a shorter t(polym). Liquid compositions polymerizing rapidly show a similar shift, and those polymerizing slowly or whose viscosity does not reach a high enough value show a small kappa peak or none. The kappa peak may be an artifact of the time dependence of heat capacity during the pulse time used for the kappa measurement, as proposed for glasses and supercooled liquids, similar to the changes in other properties observed as an artifact of kinetic freezing/unfreezing. For a polymerizing liquid, the peak may additionally arise when the rate of increase in the elastic modulus becomes equal to the rate of decrease in equilibrium Cp. In either case, its appearance does not distinguish the Brownian motions' slowing on polymerization from that on cooling or compressing a liquid.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".