A typed census of a method literature, where every count carries its denominator and every classification carries its measured precision. Absence is an empty cell against a stated population — never a bare claim that nothing exists.
A per-paper roster moves when you change the seed or the data provider — ours reordered when the forward-edge source changed. A census is bounded by camera-trap animal density and abundance estimation, so it holds still, and corrections accumulate into it instead of evaporating on the next run.
A · is a genuine gap — no work of that kind was found inside the denominator. The reliability column is not decoration: it is the measured precision of the classifier for that row, so you know which counts to trust before you use them.
| Method | method | validation | application | review | total | automated | reliability |
|---|---|---|---|---|---|---|---|
| SC-unmarked | 11 | 6 | 4 | 1 | 22 | 0 | P 31% · R 100% |
| REM | 7 | 5 | 9 | · | 21 | 0 | P 71% · R 67% |
| CT-DS | 7 | 4 | 6 | · | 17 | 3 | P 100% · R 94% |
| REST | 2 | 2 | 1 | 1 | 6 | 0 | P 80% · R 57% |
| SCR-natural-marks | 4 | · | 1 | 1 | 6 | 0 | P 33% · R 50% |
| TTE | 1 | 2 | 1 | · | 4 | 0 | P 100% · R 20% |
| SCR-genetic | · | · | 1 | · | 1 | 0 | P 100% · R 100% |
| monocular-distance | 1 | · | · | · | 1 | 0 | P 100% · R 100% |
| CTDAMS | 1 | · | · | · | 1 | 0 | P 0% · R — |
Production classifies from titles only. To test whether that is enough, two independent labellers were given strictly more information — title plus abstract — and the ground truth is where those two agree. Asking a second model whether the first was right would have been the same correlated-error trap that already produced one false result here.
A rights ledger that exempts its own sources is decoration. Each data dependency carries a verdict, and the build refuses to publish an artifact derived from a non-commercial source.