What are you seeing?Here you provide the basic data for 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 underlined words if a term you don't know shows up.
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 full case.
How to think about itMove forward in order: first the required data, then the optional measurements, and at the end confirm the full context before submitting.
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, assess its validity, completeness, consistency, and applicability to the case.
Very simple exampleAn electrical conductivity (EC) reading without a specified method, unit, or matrix is not the same as a properly traced EC, even if the number looks reasonable.