A measured effect is half the result

Plenty of the questions a study is judged on are not "what is the number" but "why is it that number": why two methods that should differ give the same gain, why an effect is larger in one regime, why the improvement vanishes past a threshold, what the failure cases have in common.

A report can measure such an effect precisely and score nothing on it, because it never says what the effect is evidence of. Numbers are the input to that argument, not the argument.

What a mechanism claim needs

• The candidate explanations, named. Usually two or three are plausible. Say

which they are before you argue for one; a single explanation asserted looks like the only one you thought of.

• Something that distinguishes them. An ablation, a stratification, a regime

where they predict different things. This is often cheap once the main result exists — you already have the pipeline.

• The one that survives, and what would overturn it. A mechanism nothing

could refute is a story.

Where it goes

In the Discussion, and again in one sentence in the Results next to the effect it explains. A reader who sees the number and no account of it forms their own, and it is rarely yours.

When you cannot explain it

Say that, and say what you would run. "We do not know why X and Y agree here; distinguishing the two accounts would need Z" is a real contribution and reads as honesty. Silence next to a surprising number reads as not having noticed it.