Investigation on the cold temperature retention capacity of the 1.5 Liter Thermos® double wall vacuum stainless steel thermal container when filled to different volumes and with different types of milk
Bibliographic record
Abstract

 Introduction: Customers sometimes question the freshness of milk inside thermal containers in coffee shops. Milk that is kept between 4°C to 60°C can support the growth of pathogens, hence it should be kept below 4°C. Thermal containers are often advertised as being able to retain the temperature of their contents for a prolonged period of time. Yet, the extent of their temperature retention capacity is not clearly defined by the manufacturers. This study investigated the effectiveness of the 1.5 Liter Thermos® Double Wall Vacuum Stainless Steel Serving Carafe thermal container in keeping milk at ≤4°C when it was filled to different volumes and with different types of milk over a nine hour period. Methods: Four tests were carried out in this study: The 1.5L Skim Milk, The 1.5L Creamo, The 0.75L Skim Milk and The 0.75L Creamo Test. For each test, the milk was placed into the 1.5L Thermos® Double Wall Vacuum Stainless Steel Serving Carafe with the initial temperature between 3.1°C to 3.4°C. Change in temperature was recorded for nine hours using the Thermocouple data logger. Results: The descriptive data demonstrates that the mean temperatures over the nine-hour period for The 1.5L Skim Milk Test, The 1.5L Creamo Test, The 0.75L Skim Milk Test and The 0.75L Creamo Test were 4.41±0.88°C, 4.51±0.95°C, 5.59±1.52°C and 6.05±1.77°C, respectively. MANOVA results suggested that “volume”, “time”, “type of milk”, “volume and time”, “volume and type of milk”, “time and type of milk”, and “volume, time and type of milk” did have effects on the temperature retention capacity of the thermal container with p-values <0.05. The temperatures of all samples were <4°C at hour zero. All of the samples’ temperatures began to increase once they were inside the thermal container and all of the samples entered the danger zone (>4°C) after four hours. A Chi Square test was conducted to determine whether Creamo or skim milk was safer (≤4°C) from hour one to four. Results showed that 123/240 (51%) skim milk and 110/240 (46%) Creamo samples were safe, but the result was not statistically significant. Conclusion: This study’s results indicate that the tested thermal container had a better cold temperature retention capacity when it was filled up (1.5L) compared to when it was only half filled (0.75L). In addition, when the thermal container was filled with skim milk, it also had a better cold temperature retention capacity compared to Creamo. Finally, this specific thermal container was not successful in maintaining the temperature of milk out of the danger zone (≤4°C) after four hours. These results should be disseminated to Environmental Health Officers whose job it is to keep the public safe from foodborne illnesses. As well, policies should be established pertaining to time permitted to keep milk in thermal containers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 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 teacher head, 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".