View: List Claim type Research area Organism Taxon as written Decade Paper Observation observed original result significant (as stated) measured Claim · model-written summary
Certain ectomycorrhizal taxa showed significant temporal variability .
Outcometemporal variability e0 Qualifiercertain ectomycorrhizal taxa e0 Verbatim
e0 “significant temporal variability was only confirmed for certain ectomycorrhizal taxa ”
✓ located verbatim in the source · abstract, characters 1126–1210 t0 “High Spatial but Low Temporal Variability in Ectomycorrhizal Community Composition in Abies alba Forest Stands ”
✓ located verbatim in the source · title, characters 0–110 Other claims from this paper (4) Observation observed original result significant (as stated) measured Claim · model-written summary
Corn had significantly less temporal yield variability than soybean or sorghum.
Outcometemporal yield variability e0 Comparatorsoybean or sorghum e0 Verbatim
e0 “Corn had significantly less temporal yield variability than soybean or sorghum. ”
✓ located verbatim in the source · abstract, characters 1216–1295 Other claims from this paper (6) Observation observed original result significant (as stated) measured Claim · model-written summary
Growing season temperature showed significant temporal variability over the last 15-20 years.
Outcometemporal variability in GST e4 Qualifierover the last 15-20 years e4 Verbatim
e4 “significant temporal variability in GST over the last 15-20 years was identified ”
✓ located verbatim in the source · abstract, characters 1045–1125 t0 “winegrape suitability analysis ”
✓ located verbatim in the source · title, characters 61–91 Other claims from this paper (3) Association observed original result significant (as stated) simulated Claim · model-written summary
Temporal variability across sowing times significantly affected soybean yield.
Treatmentdifferent sowing times e0 Not reported Direction
Verbatim
e0 “temporal variability associated with different sowing times significantly impacts soybean yield. ”
✓ located verbatim in the source · abstract, characters 1077–1173 Other claims from this paper (2) Association observed original result significant (as stated) measured Claim · model-written summary
Trait modalities related significantly to temporal and spatial habitat variability .
Outcomespecies trait modalities e0 Settingtemporal and spatial habitat variability e0 Not reported Direction
Verbatim
e0 “Patterns of species trait modalities were significantly related to temporal and spatial habitat variability ”
✓ located verbatim in the source · abstract, characters 1766–1873 t0 “higher plants comprising the Rhône floodplain vegetation ”
✓ located verbatim in the source · abstract, characters 221–277 Other claims from this paper (8) Observation observed original result significant (as stated) simulated Claim · model-written summary
Temporal variability in grapevine water needs was significant for most of the provinces.
OutcomeTemporal variability in the water needs e0 Verbatim
e0 “Temporal variability in the water needs was significant for most of the provinces ”
✓ located verbatim in the source · abstract, characters 629–710 e1 “estimate the water needs of grapevines in central Poland ”
✓ located verbatim in the source · abstract, characters 33–89 Other claims from this paper (4) Observation observed original result significant (as stated) measured Claim · model-written summary
Spatio- temporal variability in growth and survival of Ramonda myconi was rather low but significant.
Outcomegrowth and survival e4 Verbatim
t0 “Effects of regional climate and small-scale habitat quality on performance in the relict species Ramonda myconi ”
✓ located verbatim in the source · title, characters 0–111 e4 “Spatio- temporal variability in growth and survival was rather low but significant ”
✓ located verbatim in the source · abstract, characters 862–943 Other claims from this paper (6) Association observed original result significant (as stated) measured Claim · model-written summary
The optimal machine learning model for cotton LAI prediction varied with days after spraying, with significant temporal variability .
Treatmentdays after spraying e4 Outcomeoptimal machine learning prediction model e4 Not reported Direction
Verbatim
t0 “Characterizing Cotton Defoliation Progress via UAV-Based Multispectral-Derived Leaf Area Index and Analysis of Influencing Factors ”
✓ located verbatim in the source · title, characters 0–130 e4 “The optimal machine learning prediction model varied with days after spraying, demonstrating significant temporal variability ”
✓ located verbatim in the source · abstract, characters 1388–1513 Other claims from this paper (3) Observation observed original result significant (as stated) measured Claim · model-written summary
Quality characteristics varied significantly across years.
OutcomeTemporal variability was significant for quality characteristics e0 Qualifierprobably due to differences in weather conditions from year to year e0 Verbatim
t0 “APPLES ”
✓ located verbatim in the source · title, characters 63–69 e0 “Temporal variability was significant for quality characteristics, probably due to differences in weather conditions from year to year ”
✓ located verbatim in the source · abstract, characters 1195–1328 Other claims from this paper (9) Association observed original result significant (as stated) measured Claim · model-written summary
Yield variability was positively correlated with the probability of gleying from seasonal waterlogging.
Outcometemporal yield variability e0 e1 Directionpositively correlated e0 e1 Qualifierprobability of observing gleying processes associated with waterlogging for part of the year e0 e1 Verbatim
e0 “temporal yield variability is positively correlated (p < 0.05) with the probability of observing gleying processes associated with waterlogging for part of the year ”
✓ located verbatim in the source · abstract, characters 2190–2354 e1 “maize, soybean, wheat and cotton in the US Midwest ”
✓ located verbatim in the source · abstract, characters 696–746 Other claims from this paper (2) 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.