What does "confidently incorrect" mean?
A wrong answer in the tone of a right one. Ask a model for the calories in a bowl of pasta and it will usually answer with a number: no range, no question about the bowl, no note that it never saw the plate. The number may be close; the problem is that you cannot tell from the answer whether it is, because the tone is the same either way. That is the phrase r/loseit commenters used, in a thread read on 4 September 2026, alongside "yes men", for model calorie counts.
The thread's author put the mechanism plainly: the model "will give you the results with absolute certainty despite all the ways it can introduce errors". A calorie count has several of those ways, and only one of them is arithmetic. The entry can be the wrong food; the portion can be assumed; the cooking fat can be missing; the weight can be raw where the table is cooked. A model that does not say which of these it assumed has not made a small error; it has made an unverifiable one.
This page is about the figure you are given. What a model can and cannot do with a meal is its own question, and recording what it values is the third. So the question here is not whether a model can be accurate. It is whether you can see where each item's numbers came from. A number with a source is a number you can check and correct; a number without one is a number you can only believe, and "confidently incorrect" is the name for the day that belief runs out.
When is a model doing a lookup, and when is it guessing?
It depends on what you gave it. The same r/loseit author drew the line: with a description, brands and weights, a model "is basically looking up a database with some extra steps". The failure that thread and the next one describe is the photo of the plate. In a second thread, read the same day, a test of five vision models against a kitchen scale found 20 to 54 percent average error on portion size, a 50 g sweet potato guessed at 150 g, dry and cooked couscous matched wrongly, and hidden oil and butter invisible. "The models always know what the food is. They just can't tell how much is on the plate."
| What you give the model | What it can do | What it is guessing | How to read the answer |
|---|---|---|---|
| A label's figures and the grams you ate | Scale the declared values to your portion | Nothing, if it read the label right | Check the values it read back against the pack |
| A plain food with a weight, "180 g of cooked chicken breast" | Quote a reference value from what it learned, for that weight | Little; raw or cooked if you left it open | A reference figure for the grams you said |
| A dish with a size cue, "a bowl of dal, about 200 g" | Estimate from what a dal usually contains | The recipe, the ghee, the share of the pot | An estimate, useful if it says what it assumed |
| A photo of the plate | Name the dish | The portion and the fat, the two things that carry the calories | A guess until the questions are answered |
| A dish name alone, "pasta" | Give a typical figure | Everything that matters | A number that means nothing until you say how much and what it was cooked in |
Bottom line: the model is as trustworthy as the sentence you gave it, and a confident number is not evidence of a good sentence.
The PSA thread's author recommended a buffer, 20 percent on any model estimate. It is a habit born of not knowing which figures were estimates, and it is one opinion, not a measured rule. The alternative is to know.
What does IZeat change, and what does it not?
IZeat is the calorie tracker inside ChatGPT, Claude or any other assistant. Tell the assistant you already use what you ate instead of searching for foods and entering them one by one. It does not make the model more accurate; the model is still the one reading your sentence. Three different things get confused here, and it is worth keeping them apart: what a model can do on its own, what IZeat's instructions ask a connected model to do, and what IZeat actually enforces on what it stores. Only the third is a guarantee.
Enforced, by the record itself: every item carries a source, label, reference, user or estimate, and a figure without one cannot be stored at all; an estimate is stored as an estimate, and the day says which rows are. Asked for, by IZeat's instructions to the assistant, and this is the honest distinction: that a label's values are read back to you before they are recorded, because a misread, 1.2 g taken for 12 g, is a normal event and the readback is where it is caught; that one bundled question comes before an imprecise meal is estimated, about the details that would materially change the figure, the portion, the cooking fat, raw or cooked; and that a plate photo never gets a number on its own. A model that ignores an instruction still cannot store a figure without a source, and that is the difference between the two lists.
Dinner, said with the photo of a takeaway box: "This, about half of it." The assistant is asked to name the dish and to ask, in one message, what it cannot see: the size of the box, what the sauce was, whether there was rice under it. You answer, and the receipt comes back with the meal marked estimated and the day so far, and the assistant states what it assumed. A week later the day looks high; ask what is in that dinner and the rows come back with their sources, and the estimated ones are the first to question. "The box was 350 g, not 500" corrects the row, and the earlier state stays in the meal's history.
What does a source not tell you?
What a source is not: a source is not a guarantee. A label can be misread past the readback, a reference table is an average, and an estimate is an estimate. What the rules give you is a record where you can see which figures were which, and the accuracy article goes through what to do with that. Trust, on those terms, is a habit: read the receipt, question the estimated rows, correct in one sentence.
Frequently asked questions
Short answers to the questions people type, each one sourced above.
Why does a wrong calorie count sound the same as a right one?
Because a model answers in the tone that was asked for, and a request for a number gets a number. Nothing in the reply marks which parts were read, looked up or guessed, so the confident figure for a weighed chicken breast and the confident figure for a photographed plate look alike. The size of the error is not the failure; the missing source is, and it is what a record can add.
Should I add a buffer to AI calorie estimates?
One r/loseit author recommended adding 20 percent to any model estimate, a habit born of not knowing which figures were guesses; it is community opinion, not a rule IZeat gives. Through IZeat the alternative is to know: each item carries its source, the estimated rows are marked, and the assistant is asked what it assumed. Whether to pad an estimate is then a decision you make row by row, not a blanket rule.
Does IZeat make ChatGPT more accurate?
No. The model still reads your sentence and still cannot see a portion in a photo. What IZeat changes is the rules around the figure: a source on every item, an estimate recorded as one, the assistant asked to read label values back before they are stored, and a bundled question before any imprecise meal is estimated. A figure without a source cannot be stored at all. The accuracy is in the input; IZeat makes the input's quality visible.
How do I check a calorie count the assistant gave me?
Read the receipt, not the chat around it. It names each item, its grams and its source; a label row can be checked against the pack, a reference row against the weight you said, an estimated row against what the assistant said it assumed. Ask what is in a meal and the rows come back with their sources. If a figure is wrong, say the right one; the row is corrected and the earlier state stays in the history.
Is Claude any different from ChatGPT here?
Not in kind. A model asked for a figure tends to give one, and no model can see a portion in a photo. The difference IZeat introduces is the same for every assistant it connects to: the source on each item, the readback of a label, the question before an estimate. Which assistant reads your sentence better on a given day is not something IZeat measures or claims.