logistic
logistic: 7 implementations from 7 papers ran on one shared input (census 2026-09-22, battery b986f7e04d79); they produced 6 distinct outputs across 4 buckets, one shared input per bucket.
Identical values to six decimals (the recorded digest) on the shared input are agreement on those inputs, not equivalence. Implementations are compared only within one bucket, the positional (rank, kind, dtype) of each array argument; the argument name is not part of the key because the harness draws the shared array from (rank, kind) and casts it to the dtype, whatever the name; each bucket's shared input is fixed by that key, so members of one bucket saw bitwise-identical inputs under their own scalar arguments. A cluster is the set of members whose recorded output digest is identical. Nothing here says which computation a paper's method intended, and nothing reproduces a paper's results.
Not compared, and not in the tables or the counts above:
- Every examined implementation of this name that took an array argument ran on the shared input.
- 1 more implementation from 1 paper took no array argument and ran only on its own fixture arguments; no shared input existed for it, so it is not compared (on 1 the recorded shared-output digest is the own-fixture digest).
- Every compared output was digested.
Bucket 1 of 4: arg 1: rank 1, kind float, dtype float64
4 implementations from 4 papers share this bucket (rank, kind, dtype of each array argument, positional; each member's recorded signature, argument name included, is shown under it); 3 distinct outputs, largest cluster first. Values are the first 8 of the recorded output, flattened.
| Cluster (same digest to six decimals) | Members | Shared output on this bucket's input |
|---|---|---|
| 2 implementations 2 papers 2091c6f76ede recorded values identical |
yolo_detection.py 74cfca8a recorded val:1/float/float64
inference/candidate_selection.py c6072629 recorded x:1/float/float64 |
[0.288252, 0.539202, 0.710459, 0.31817, 0.45605, 0.513255, 0.164044, 0.455733] shape [8] · float64 · ndarray |
| 1 implementation 1 paper 3df338495baa |
fairness_project/solver.py 36a1468d recorded x:1/float/float64 |
[0.340031, 0.774796, 1.23946, 0.382975, 0.608898, 0.720015, 0.179179, 0.608315] shape [8] · float64 · ndarray |
| 1 implementation 1 paper 409910e5ff51 |
src/calibration.py d89e5cb2 recorded x:1/float/float64; L=1.0, k=2.0, m=0.5 |
[0.0569053, 0.334982, 0.688952, 0.0741659, 0.20546, 0.290298, 0.0139685, 0.205043] shape [8] · float64 · ndarray |
Bucket 2 of 4: arg 1: rank 1, kind float, dtype float64 · arg 2: rank 2, kind float, dtype float64
1 implementation from 1 paper share this bucket (rank, kind, dtype of each array argument, positional; each member's recorded signature, argument name included, is shown under it); 1 distinct output, largest cluster first. Values are the first 8 of the recorded output, flattened.
| Cluster (same digest to six decimals) | Members | Shared output on this bucket's input |
|---|---|---|
| 1 implementation 1 paper e2ca717ff7cf |
PeerLoss.py 602ea0b6 recorded w:1/float/float64, x:2/float/float64 |
[0.541297, 0.807698, 0.73564, 0.967772] shape [4] · float64 · ndarray |
Bucket 3 of 4: arg 1: rank 2, kind float, dtype float32
1 implementation from 1 paper share this bucket (rank, kind, dtype of each array argument, positional; each member's recorded signature, argument name included, is shown under it); 1 distinct output, largest cluster first. Values are the first 8 of the recorded output, flattened.
| Cluster (same digest to six decimals) | Members | Shared output on this bucket's input |
|---|---|---|
| 1 implementation 1 paper a4f377964998 |
src/fair_model.py d47d2823 recorded x:2/float/float32 |
[1.95523, 0.195336, 0.959239, 0.406219, 0.340331, 0.305158, 0.415697, 1.02007, …] shape [4, 8] · float32 · Tensor |
Bucket 4 of 4: arg 1: rank 2, kind float, dtype float64
1 implementation from 1 paper share this bucket (rank, kind, dtype of each array argument, positional; each member's recorded signature, argument name included, is shown under it); 1 distinct output, largest cluster first. Values are the first 8 of the recorded output, flattened.
| Cluster (same digest to six decimals) | Members | Shared output on this bucket's input |
|---|---|---|
| 1 implementation 1 paper cac27aad11ab |
ssm/emissions.py e236f0c0 recorded x:2/float/float64 |
[0.858469, 0.177442, 0.616815, 0.333836, 0.288465, 0.262993, 0.34012, 0.63943, …] shape [4, 8] · float64 · ndarray |
Identical values to six decimals (the recorded digest) on the shared input are agreement on those inputs, not equivalence; where a cluster's members carry recorded values, the largest difference among them is shown under the cluster. Paper titles are the archive's archive 2025-07-28 where the paper is in the archive and the graph's where it was added by Syntology; papers with no page here are shown by their recorded paper id only. A paper count above the implementation count means one implementation (one code sha) is held from several papers' repositories and counts once. Per-sample status, licence and fingerprint records for each paper are on its paper page. JSON twin: /census/logistic.json.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections