ANÁLISES DESCRITIVAS E MICROBIOLÓGICAS DAS ÁGUAS MINERAIS ENVASADAS E COMERCIALIZADAS NA REGIÃO METROPOLITANA DE RECIFE-PE.
Bibliographic record
Abstract
The paper aims to describe the quality of mineral water marketed by the population of the metropolitan area of Recife-PE in 2015, regarding the microbiological and descriptive analyzes. We analyzed 70 samples of seven different brands of bottled mineral water in the period from January to April and June to August due year. The samples were divided into thirty-five units for both periods, according to Standard Methods for the Examination of Water and Wastewater, by means of testing the presence or absence (P-A) and Pour Plate Method. Regarding the microbiological analysis of samples of the first period in accordance with Resolution 275/2005 brands A, B and C had their departures REJECTED samples and the marks D, E, F and G were APPROVED. In the second period the marks A, B, C, D and E had their departures REJECTED samples and the F and G brands were APPROVED. The percentage shown in the first period indicates 57.14% (APPROVED) and 42, 85% (REJECTED). In the second period the percentage indicates that 28.75% (APPROVED) and 71.42% (REJECTED). That is, in the second period there was obtained a high percentage of water which has been rejected due to the presence of microbiological bacteria.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".