Bibliographic record
Abstract
Arsenic determination in some marine algae of British Columbia was carried out by using Hydride Generation and Graphite Furnace Atomic Absorption Spectrometzy (HGAAS and GFAAS) following a two-hour wet digestion procedure. The total arsenic concentration in Fucus distichus and other brown algae determined by using the continuous HGAAS was found to vary with species and the collection sites, ranging from 1.8 μg/g As to 36.9 μg/g As (dry weight basis). Similarly, the arsenic concentrations determined in red algae were found to vary from a low 1.3 μg/g As to a high 39.7 μg/g As (also on a dry weight basis). Also, the arsenic concentrations determined in green algae were found to vary quite widely as in the other two classes of macroalgae, ranging from 0 μg/g As (not detected) to 27.2 μg/g As. These widely varying arsenic concentration results suggest that the amount of arsenic accumulated by seaweed is not only related to the class of the macroalgae as well as the particular species, but also to the sampling location and its soil conditions. Both the continuous HGAA and the semi-continuous HG-GC-AA techniques were employed for the examination of the selective reduction of four arsenic species, namely arsenate [As(V)], arsenite [As(III)], monomethylarsonic acid (MMAA) and dimethylarsinic acid (DMAA). The response profiles of the four arsenic species were plotted and the optimum arsenic analytical conditions were determined from these plots. By using a combination of extraction followed with sodium hydroxide digestion of the freeze dried seaweed, the reducible and “hidden” arsenic species in the extracts and digests were determined by using the semi-continuous mode HG-GC-AAS. Greater than 90% of the total arsenic in the seaweeds was found in the “hidden” arsenic forms. On-line detection techniques of High Performance Liquid Chromatography Microwave Oven Assisted Decomposition Hydride Generation Atomic Absorption Spectrometry (HPLC-Mic-HGAAS) and High Performance Liquid Chromatography Inductively Coupled Plasma Mass Spectrometry (HPLC-ICPMS) were employed for the characterization of arsenic species in water soluble extract of F. distichus collected from Head of Hastings Arm, British Columbia. Prior to the use of these techniques for arsenic species identification, arsenic containing fractions were isolated via the use of several combinations of chromatographic procedures such as gel permeation chromatography (gpc), ion exchange chromatography (IEC), thin layer chromatography (tlc) and reverse phase high performance liquid chromatography (HPLC). The water soluble extract of F. distichus was found to contain two major arsenosugars*, 11a and 11b, as well as several minor, unidentified arsenic species, likely to be other arsenosugar derivatives. The biotransformation studies of “hidden” organoarsenicals in F. distichus were carried out by using anaerobic decomposition conditions in “open” and “closed” systems. Two arsenic species, 2-dimethylarsinylethanol (DMAE) and dimethylarsiic acid (DMAA) were identified from the “open” system decomposition products by using the HPLC ICPMS technique. In the “closed” system, DMAE was characterized as a major decomposition product and DMAA was observed as another main component. Other minor arsenic species were found in the decomposition products, however, these were not identified. [chemical compound diagrams]
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".