In situ gold adsorption experiment at an acidic hot spring using a blue-green algal sheet
Bibliographic record
Abstract
Abstract Gold (Au), as one of the most precious metal resources that is used for both industrial products and private ornaments, is a global investment target, and mining companies are making huge investments to discover new Au deposits. Here, we report in situ Au adsorption in an acidic hot spring by a unique adsorption sheet made from blue-green algae with a high preferential adsorption ability for Au. The results of in situ Au adsorption experiments conducted for various reaction times ranging from 0.2 h to 7 months showed that a maximum Au concentration of 30 ppm was adsorbed onto the blue-green algal sheet after a reaction time of 7 months. The Au concentration in the hot spring water was below the detection limit (< 1 ppt); therefore, Au was enriched by preferential adsorption onto the blue-green algal sheet by a factor of more than ~ 3 × 107. Thus, our gold recovery method has a high potential to recover Au even from an Au-poor solution such as hot spring water or mine wastewater with a low impact on the environment.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".