Definitions: landing_order

17 gate-passed questions · 12 cells · 8 occupied · go to this type's cells

Bins were cut on this corpus at 240×135@16 (CLEAR_PX 25, motion floor 19 px). Margin bins: a near-edge band [1, 1.25) above the gate boundary, then corpus quantiles; salience bins: a visibility floor, then quantiles.

Axis 1 — margin (the gate quantity as a clearance ratio; ≥ 1 passes)

landing gap (frames) / 3; 'same': one bin · measurable on 15 questions

margin binnumeric range
near-edge [1,1.25)[−∞, 1.25)
bin0[1.25, ∞)
state:same(state / single bin)

Ask: is this the same quantity the gate certifies on for this type? Are the states (e.g. 'same', 'gone') the right one-bin exceptions? Are the edges where a change in difficulty actually happens?

Axis 2 — salience (how visible / how large the motion is)

min queried-object peak area (frac of frame) · floor 0.0007716

salience binnumeric range
<floor (0.0008)[−∞, 0.0007716)
bin0[0.0007716, 0.008827)
bin1[0.008827, 0.01404)
bin2[0.01404, ∞)

Ask: does this axis capture what makes a question of this type perceptually hard, independently of the answer? Is the floor the right anti-gaming boundary?

Axis 3 — context

branch 2 spread default: n_airborne_ever (cv) · labels: bin2

Compatible margin bins per context label (cells outside these are definitionally impossible):

Answer distribution (gate-passed)

answern
neither lands before the video ends3
the green cube2
the green cylinder2
the orange ball2
the yellow ball2
they land at the same time2
the red-and-green striped cube1
the blue cone1
the red-and-purple striped cube1
the blue-and-yellow striped cylinder1

Type-level verdict