What are you seeing?Here you give the basic data of your own temporary case. If you don't know something, leave it blank instead of making it up.
Why it mattersYolia needs to distinguish what you know with certainty from what is still missing, so as not to misinterpret your case.
How to think about itComplete one screen at a time and read the help for each field; Tap the underlined words if a term you don't know appears.
Very simple exampleIf you don't know the actual pH of your substrate, don't enter "7" just to fill the field — leave it empty and Yolia will treat it as a missing data point, not a measured one.
What are you seeing?The form separates identity, stage, objectives, environment and measurements into independent blocks.
Why it mattersEach block reduces ambiguity before Yolia interprets the entire case.
How to think about itMove forward in order: first the required data, then the optional measurements, and finally confirm the full context before sending.
Very simple exampleA missing measurement only reduces the confidence of the result; a made-up measurement can lead Yolia to a directly wrong conclusion.
What are you seeing?The intake preserves the origin of each data and distinguishes between declared, measured and absent data.
Why it mattersThe quality of the input directly limits the inferential quality of all subsequent analysis — none of this is cosmetic.
How to think about itBefore treating any value as evidence, evaluate its validity, completeness, consistency, and applicability to the case.
Very simple exampleAn electrical conductivity (EC) without a specified method, unit, or matrix is not equivalent to a correctly drawn EC, even if the number seems reasonable.