View: List Claim type Research area Organism Taxon as written Decade Paper Method / resource observed original result positive measured Claim · model-written summary
The YOLOv4 detection platform reached a recall rate ( Recall ) of 97.35% for wheat seed germination.
recall rate (Recall) e1 Verbatim
e5 “rapid and accurate detection of wheat seed germination ”
✓ located verbatim in the source · abstract, characters 485–539 e1 “a recall rate ( Recall ) of 97.35% ”
✓ located verbatim in the source · abstract, characters 1396–1428 Other claims from this paper (4) Method / resource observed original result positive measured Claim · model-written summary
Instance segmentation reached a mean average recall rate ( recall @50:95) of 84.5%.
mean average recall rate (recall@50:95) e3 Verbatim
t0 “Classification of Coffee Leaf Plant ”
✓ located verbatim in the source · title, characters 26–61 e3 “the mean average recall rate ( recall @50:95) was 84.5% ”
✓ located verbatim in the source · abstract, characters 1551–1604 Other claims from this paper (3) Method / resource observed original result positive measured Claim · model-written summary
Mean class recall was 100.0%.
Not reported Taxon
Verbatim
e0 “and recall 100.0% ”
✓ located verbatim in the source · abstract, characters 1204–1221 Other claims from this paper (5) Method / resource observed original result positive measured Claim · model-written summary
Precision- recall analysis indicated balance between classification precision and recall .
equilibrium between accurate classification and recall of information e0 Not reported Taxon Comparator Value
Verbatim
e0 “the precisionrecall study highlighted the model's equilibrium between accurate classification and recall of information. ”
✓ located verbatim in the source · abstract, characters 1150–1270 Other claims from this paper (4) Method / resource observed original result positive measured Claim · model-written summary
Xception had 94% recall .
Verbatim
e0 “recall (94%) ”
✓ located verbatim in the source · abstract, characters 1061–1073 Other claims from this paper (5) Method / resource observed original result mixed measured Claim · model-written summary
YOLOv7 with ADAM traded some precision for recall .
precision-recall trade-off e0 Verbatim
e0 “The YOLOv7 ADAM exhibits a precision- recall trade-off, with precision being slightly sacrificed for recall ”
✓ located verbatim in the source · abstract, characters 632–738 Other claims from this paper (4) Method / resource observed original result measured Claim · model-written summary
The model achieved 94% recall .
Verbatim
e0 “94% recall ”
✓ located verbatim in the source · abstract, characters 848–858 t0 “crop ”
✓ located verbatim in the source · title, characters 67–71 Other claims from this paper (5) Method / resource observed original result positive measured Claim · model-written summary
Training recall was 95%.
Verbatim
e0 “recall 95% ”
✓ located verbatim in the source · abstract, characters 811–821 Other claims from this paper (7) Method / resource observed original result positive measured Claim · model-written summary
Testing recall was 90%.
Verbatim
e0 “recall 90% ”
✓ located verbatim in the source · abstract, characters 897–907 Other claims from this paper (7) Method / resource observed original result positive measured Claim · model-written summary
The LDSL framework achieved 94.44% recall in wheat disease recognition, higher than ConvNeXt-T (92.66% recall ).
Verbatim
t0 “wheat disease detection ”
✓ located verbatim in the source · title, characters 65–88 e4 “a recall of 94.44% ”
✓ located verbatim in the source · abstract, characters 1414–1432 e2 “such as ConvNeXt-T (92.66% accuracy, 92.69% precision, 92.66% recall , and 92.63% F1) ”
✓ located verbatim in the source · abstract, characters 1546–1630 Other claims from this paper (8) Lexical search (BM25). All words must match; if nothing does, any word. Organism names also match every spelling of the same organism. No semantic search yet.
Triticum aestivume5
Coffea