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For WAZMING BLANKETS/LINEN o R or Solutions SOLUTIONS MUST 136 . 197 EXTERNAL ાર્ટ હ ONLy ,

All Olympic Warmettes are essentially double walled, insulated cabinets with transparent doors. The Warmettes normally remain on continuously. The temperature is user selectable. The Model 10 uses a resistance element heater encapsuled in a high temperature r lie Model 10 uses a roclocanos element of the interior. Due to the small size, forced air circulation is not needed. The Models 30, 31 and 40 make use of a fan to force recirculating air past The Models 50, of and 10 make see above the main chamber) and then into the resistence heating bientified (roothe heaters via an air duct built into the left wall. The Models 31 and 40 differ from the Model 30 in two respects: · The selectable maximum temperature is higher. - · The delivery duct/plenum inside the right wall is more efficient, allowing the Models 31 and 40 to operate at the higher temperatures.

The provided document is a 510(k) premarket notification letter from the FDA regarding a medical device called "Warmette" by Olympic Medical. It is a Class I device, a powered heating unit intended for warming blankets/linen or external solutions.

Based on the provided text, the device Warmette (Models 30, 31, and 40) meets acceptance criteria primarily through nonclinical testing, demonstrating substantial equivalence to a predicate device (Olympic Warmette Model 10). There is no mention of a study involving human readers or clinical trials for performance evaluation in the context of typical AI/diagnostic device acceptance criteria. The device is a heating cabinet, not an AI or diagnostic tool.

Here's a breakdown of the requested information based on the document:

1. A table of acceptance criteria and the reported device performance

The document doesn't explicitly state "acceptance criteria" in a formal table with pass/fail thresholds for specific performance metrics in the way one would see for a diagnostic device. Instead, it demonstrates performance by comparing its specifications to a predicate device and verifying certain safety functions. The key performance parameter is temperature range and accuracy.

¹ Preliminary specifications, will not exceed the range of the predicate device (75° - 150°F)

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

This information is not applicable as the device is a heating unit, not a diagnostic or AI-driven device with a "test set" in the context of patient data. The "tests" refer to engineering and safety verification.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This information is not applicable. The "ground truth" for a heating unit involves physical measurements and engineering standards, not expert medical interpretation of data.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

This information is not applicable. Adjudication methods are relevant for ambiguous diagnostic findings, which is not relevant to this device.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

This information is not applicable. An MRMC study is relevant for AI-assisted diagnostic tools. This device is a powered heating unit, not an AI or diagnostic device.

6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done

This information is not applicable. This device does not involve an algorithm or AI.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

The "ground truth" in this context is based on engineering specifications, physical measurements, and compliance with recognized safety standards. For example, a thermometer would be used to verify the actual temperature of the unit and its contents, and electrical testing equipment would verify electrical safety parameters.

8. The sample size for the training set

This information is not applicable. The device is not an AI/machine learning model, so there is no "training set."

9. How the ground truth for the training set was established

This information is not applicable. There is no training set for this device.

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