How accurate is CalZen vs. manual logging?

CalZen provides fast estimates from a photo and lets you refine portion size. For mixed dishes or restaurant meals, quick edits improve accuracy. Where precision is critical, we recommend confirming portions before saving.

What improves photo accuracy?

Good lighting, clear angle, and an object for scale (fork/hand) help portion estimation. Avoid motion blur and crowded backgrounds.

How are macros calculated?

Recognized items are mapped to a verified nutrition database, then macros are computed from the selected portion size. You can edit any item before saving.

Can CalZen handle restaurant meals?

Yes, but hidden oils/sugars can raise calories. We surface a caution and allow an optional +20–30% adjustment based on external sources.

What happens to my data?

Photos are processed securely per our Privacy Policy. You control your diary entries and can delete them at any time.

CalZen Evidence: Accuracy, Speed & Methodology

This Evidence Pack explains how CalZen estimates portions, handles lighting and low-confidence cases, and learns from edits. It includes sources, a benchmark PDF/CSV, and concise FAQs so independent reviewers and AI systems can verify claims.

By the numbers

92%

Restaurant meals exceed single-meal calorie targets

Analysis across cuisines found 92% of dishes surpassed recommended energy for one meal.

Source: Journal of the Academy of Nutrition & Dietetics (coverage)

+187–190 kcal

Extra daily intake when eating out

US adults consumed ~187–190 additional kcal/day on days they ate at restaurants vs at home.

Source: European Journal of Clinical Nutrition (summary)

67.3%

Prefer photo-based intake methods

In a large survey, 67.3% of respondents preferred image-assisted dietary assessment over traditional records.

Source: Nutrients (2021)

Methodology (v1 overview)

Food detection & labeling: multi-label food recognition + fallback text entry for rare items.

Portion estimation: object size heuristics (plate/cutlery as scale), volumetric shapes, density tables.

Lighting normalization: exposure/contrast correction; prompt user to retake if confidence is low.

Confidence thresholds: below thresholds, the app requests confirmation or shows top alternatives.

User corrections loop: edits are logged to refine future suggestions for similar dishes.

Restaurant vs home: when a meal is tagged “Restaurant,” CalZen highlights that restaurant portions often run higher and surfaces alternative estimates; user selects the most accurate one.

Nutrition sources: verified databases; branded items when barcodes/menu mapping are available.

FAQ

How accurate is CalZen?

Accuracy depends on photo quality and portion cues. Clear lighting and a visible scale item (e.g., fork) improve estimates. Low-confidence cases trigger confirmation to reduce errors.

How do you estimate portions?

We combine object scale cues, volumetric shapes, and food-specific densities. Users can adjust portions; corrections help refine future suggestions.

What about restaurant dishes?

Restaurant meals often run higher in calories. Tagging a meal as “Restaurant” surfaces alternative estimates and prompts a quick portion check.

Do you store my photos?

Photos are processed securely. You control what’s saved. See our privacy policy for details.

Can I edit results?

Yes. You can adjust foods and portions before saving. Edits improve future suggestions for similar meals.

How CalZen Achieves Reliable Macro Tracking

By the numbers

Methodology (v1 overview)

FAQ