Test avec deux technique d`alcalinité disponible dans le marché pour stimuler la croissance de coraux (étape 1) et développement de une formule mathématiques prédictive de la dose et consumation de l`alcalinité (PPM CaCO3) (étape 2)
Bibliographic record
Abstract
In most corals, the autotrophic process is more important than the heterotrophic. Tremblay (2012) proved that the transfer of carbonate during the photosynthesis of zooxanthellae is of 50-90% and, during the coral bleaching phenomenon, the heterotrophic process is not enough to substitute the carbonate supplied by the zooxanthellae.During the care of corals in captivity, there are several parameters that need to be frequently monitored. Two of the parameters that change the most are alkalinity and calcium, which are continuously consumed by the corals.In the stage 1 of this research, we tested two methodologies to supply alkalinity to the coral growing systems in Aquanov Canada, with the purpose of optimizing the production.During six months, we tested two different sources of alkalinity.1. Calcium reactor during the first three months.2. KH booster solution of the company Aquaristik (calcium carbonate) during 3 months.The answer to the two sources of alkalinity on two species of corals Montlpora sp and Acropora sp was studied. The test was carried out on 10 corals of each species. The variables that were measured were the Aquanov Index, mortality and alkalinity concentration.After three months working with the calcium reactor technique as source of alkalinity, the results of the Aquanov health index for corals of Acropora sp was of 6.2 (+/· 0.9) and for Montiporo sp, of 6.4 (+/-1.2), which fall within the regular good classification within the Aquanov index range. With the same technique, the results of the alkalinity concentration were of 8.2 (+/- 0.7). The color of the corals was the most affected indicator; the value for Montipora sp was of 1.7 (+/- 0.5) and for Acropora sp, of 1.3 (+/- 0.5).The results of the Aquanov index with the alkalinity dosage through thI r KH booster solution (sodium carbonate) were better. For Montipora sp, the Aquanov index was 8.0(+/- 0.7) and for Acropora sp, 7.9 (+/· 0.7); both values are classified as good. The color indicator has raised for both species to values of 2.8 (+/· 0.4) for Montipora sp and 2.9 (+/· 0.3) for Acropora sr.The alkalinity concentration in water was low in the first 30 days, with an average of 7.2 (+/· 2.1) dKH, but during the second and third month it was very good, of 9.4 (+/-0.7) dKH.In conclusion, in this stage we found out that the best technique to maintain optimum levels of alkalinity in the coral systems in the Aquanov installations was de dosage with KH booster (calcium carbonate), as its usage resulted in a very good coloration of the corals, very good values of the Aquanov health index and very good alkalinity concentrations.During the second stage, we aimed at developing mathematical formulas to achieve a better dosage of the KH booster solution.After carrying out several analysis and calculations, we developed two mathematical formulas based on the initial and final concentration of alkalinity in dKH and the initial concentration of KH booster. The two formulas were used for the two main coral growing systems of Aquanov. The formulas were the following:1. System 1. Volume added (Va) : (10 dKH-(dKH concentration)) x 537.2. System 2. Volume added (Va) : (10 dKH-(dKH concentration)) x 268.5.When testing the formulas in the systems, we discovered that the alkalinity values reached were the expected but with certain standard deviation. For system 1, the average standard deviation was of +/· 0. 7 dKH and for system 2, +/· 0.5 dHK.At the end of the study, we discovered that the mathematical formulas were very useful for the dosage of alkalinity in the coral growing systems in Aquanov installations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".