The Measurement of Solute Diffusion Coefficients in Dilute Liquid Alloys: The Influence of Unit Gravity and <i>G</i>‐Jitter on Buoyancy Convection
Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
Liquid diffusion experiments conducted on the MIR space station using the Canadian Space Agency QUELD II processing facility and the microgravity isolation mount (MIM) showed that g-jitter significantly increased the measured solute diffusion coefficients. In some experiments, milli-g forced vibration was superimposed on the sample when isolated from the ambient g-jitter; this resulted in markedly increased solute transport. To further explore the effects arising in these long capillary diffusion couples from the absence of unit-gravity and the presence of the forced g-jitter, the effects of a 1 milli-g forcing vibration on the mass transport in a 1.5 mm diameter long capillary diffusion couple have been simulated. In addition, to increase understanding of the role of unit gravity in determining the extent to which gravity can influence measured diffusion coefficient values, comparative experiments involving gold, silver, and antimony diffusing in liquid lead have been carried out using a similar QUELD II facility to that employed in the QUELD II/MIM/MIR campaign but under terrestrial conditions. It was found that buoyancy-driven convection may still persist in the liquid even when conditions are arranged for a continuously decreasing density gradient up the axis of a vertical long capillary diffusion couple due to the presence of small radial temperature gradients.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".