alabnii/sciclaimeval-shared-task huggingface dataset:
Claim: Our results indicate significant correlations between the peak angular momentums of the attack arm, non-attack arm, non-attack leg, forearm, and hand with the arm swing speed at BI ( Table 1 ).
Evidence type: table
Evidence caption: Table 1: Peak angular momentum variables and correlations with the arm swing speed at ball impact (BI).
Context: This study investigated the relationships between angular momentum variables and swing hand speed during jump serve aerial spiking, utilising correlation and regression analyses.
Verdict: Supported
Claim: The peak angular momentum of the non-attack leg (−0.026 ± 0.012 s –1 ) exhibited negative correlations with the arm swing speed at BI ( Table 1 ).
Evidence type: table
Evidence caption: Table 1: Peak angular momentum variables and correlations with the arm swing speed at ball impact (BI).
Context: In the later part of the arm-cocking phase, the angular momentums of the attack and non-attack legs simultaneously rotated clockwise (−).
Verdict: Supported
Claim: There was no significant difference in BMD between the two groups ( P > 0.05).
Evidence type: table
Evidence caption: Table 4: Comparison of two groups of BMD and abnormal rates.
Verdict: Supported
Claim: There was no difference in the prevalence of osteoporosis and low bone mass rate between the two groups, indicating that there was no significant difference in BMD between the two groups ( Table 4 ).
Evidence type: table
Evidence caption: Table 4: Comparison of two groups of BMD and abnormal rates.
Context: There was no significant difference in BMD between the two groups ( P > 0.05).
Verdict: Supported
Claim: Additionally, 46.6% of participants were primary school graduates, 9.4% reported alcohol use, and 13% were smokers, with an average duration of smoking of 22.83 ± 6.94 years.
Evidence type: table
Evidence caption: Table 1: Participants’ personal data, IIEF total score (n= 223).
Context: Table 1 presents the personal data of the participants along with the total score of IIEF. The participants had a mean age of 63.26 ± 7.62 years, with 97.3% being married.
Verdict: Supported
Claim: The mean duration of hypertension was 7.92 ± 4.06 years, and the most commonly used medication among participants (27.8%) was ACE Inhibitors.
Evidence type: table
Evidence caption: Table 1: Participants’ personal data, IIEF total score (n= 223).
Context: Table 1 presents the personal data of the participants along with the total score of IIEF. The participants had a mean age of 63.26 ± 7.62 years, with 97.3% being married. Additionally, 46.6% of participants were primary school graduates, 9.4% reported alcohol use, and 13% were smokers, with an average duration of smoking of 22.83 ± 6.94 years.
Verdict: Supported
Claim: Notably, 81.6% of participants had erectile dysfunction, with the mean IIEF total score indicating a mild level of dysfunction (18.72 ± 3.60) ( Table 1 ).
Evidence type: table
Evidence caption: Table 1: Participants’ personal data, IIEF total score (n= 223).
Context: Table 1 presents the personal data of the participants along with the total score of IIEF. The participants had a mean age of 63.26 ± 7.62 years, with 97.3% being married. Additionally, 46.6% of participants were primary school graduates, 9.4% reported alcohol use, and 13% were smokers, with an average duration of smoking of 22.83 ± 6.94 years. The mean duration of hypertension was 7.92 ± 4.06 years, and the most commonly used medication among participants (27.8%) was ACE Inhibitors.
Verdict: Supported
Claim: Significant negative correlations were observed between age and the IIEF total score, as well as between the duration of hypertension and the IIEF total score ( p < 0.05).
Evidence type: table
Evidence caption: Table 3: Correlation between age, duration of hypertension, duration of smoking and IIEF total.
Context: Table 3 displays the correlation between age, duration of hypertension, duration of smoking, and the IIEF total score.
Verdict: Supported
Claim: Regarding methodological quality assessment tools, 12 studies utilized the Cochrane Collaboration Network RoB risk assessment tool, four employed the PEDro scale, one used the Cochrane Collaboration Network RoB and PEDro, and one applied the EPHPP for risk assessment.
Evidence type: table
Evidence caption: Table 1: Basic characteristics of the literature included in the study.
Context: The included meta-analyses were published between 2018 and 2023, and all the original studies were randomized and controlled. The largest study included 2,526 participants and the smallest had 182 participants, involving a total of 18,461 individuals. The interventions in the trial groups consisted of aerobic, physical, mental, resistance, and multipart exercises. The control group in the randomized trials maintained their regular daily activities without any specific exercise interventions.
Verdict: Supported
Claim: However, percentage of population that were married had statistically significant low diabetes-related ED visit rate ( Table 5 ).
Evidence type: table
Evidence caption: Table 5: Results of a multivariable negative binomial regression model examining the associations between county characteristics and the rate of diabetes-related emergency department visits in Florida, 2019.
Context: Based on the final multivariable negative binomial model, the following independent variables had significant high county-level non-gestational diabetes-related ED visit rates: percentages of population who were non-Hispanic Black, current smokers, had diabetes, and had no insurance coverage ( Table 5 ).
Verdict: Supported
Claim: A comparative analysis of hematology parameters indicated that children exposed to lead had significantly lower values of monocytes, basophil, hemoglobin, red blood cell count (RBC), hematocrit (HCT), MCH, MCHC, mean platelet volume (MPV), and platelet volume distribution width (PDW), and higher white blood cell count (WBC), neutrophils, eosinophil, red cell distribution width coefficient of variation (RDW-CV), RDW-SD, platelet, and plateletcrit (PCT) levels compared to healthy children ( Table 1 ).
Evidence type: table
Evidence caption: Table 1: Hematologic parameters of the lead-poisoned children and the healthy controls.
Verdict: Supported
Claim: For SU kinematics, C4 exhibited the largest horizontal displacements for the pelvis, femur, knee, and lower leg, all significantly higher than other clusters ( p < 0.001).
Evidence type: table
Evidence caption: Table 2: Comparisons of features between the clusters classified by Louvain clustering unsupervised machine learning.
Context: To validate the quality and distinctiveness of the Louvain clustering solution, we calculated widely-used cluster validity indices. The Davies–Bouldin index was 2.09, and the Calinski–Harabasz index was 59.26. While the Davies–Bouldin index was somewhat high (lower values indicate better separation), the Calinski–Harabasz index supported the presence of distinct groupings in our data. The Louvain clustering algorithm identified four distinct clusters (C1–C4) with significant differences in all features (all p < 0.001, except for AHD-SU ( p = 0.017) and portion of EOA ( p = 0.019)) ( Table 2 ). Tukey’s post-hoc analysis revealed that those in C2 had the youngest age (44.80 ± 11.30 years, p < 0.001 vs. all other clusters) and highest BMI (25.59 ± 2.42, p < 0.001 vs. all other clusters). C2 included exclusively males, whereas the other clusters had a mixed sex composition.
Verdict: Supported
Claim: C1 exhibited negative mean values for the knee and lower leg displacements during SD, significantly different from other clusters ( p < 0.001).
Evidence type: table
Evidence caption: Table 2: Comparisons of features between the clusters classified by Louvain clustering unsupervised machine learning.
Context: To validate the quality and distinctiveness of the Louvain clustering solution, we calculated widely-used cluster validity indices. The Davies–Bouldin index was 2.09, and the Calinski–Harabasz index was 59.26. While the Davies–Bouldin index was somewhat high (lower values indicate better separation), the Calinski–Harabasz index supported the presence of distinct groupings in our data. The Louvain clustering algorithm identified four distinct clusters (C1–C4) with significant differences in all features (all p < 0.001, except for AHD-SU ( p = 0.017) and portion of EOA ( p = 0.019)) ( Table 2 ). Tukey’s post-hoc analysis revealed that those in C2 had the youngest age (44.80 ± 11.30 years, p < 0.001 vs. all other clusters) and highest BMI (25.59 ± 2.42, p < 0.001 vs. all other clusters). C2 included exclusively males, whereas the other clusters had a mixed sex composition. For SU kinematics, C4 exhibited the largest horizontal displacements for the pelvis, femur, knee, and lower leg, all significantly higher than other clusters ( p < 0.001). During SD, C3 showed the largest pelvis and femur displacements, while C4 had significantly higher ankle displacement ( p < 0.001 vs. all other clusters).
Verdict: Supported
Claim: The baseline characteristics were described in Table 1 . For women <35 years old, the median age for the HRT group and GnRH-a group were 30.6 and 31.3 years, respectively.
Evidence type: table
Evidence caption: Table 1: Demographic characteristics of patients between different age groups and endometrial preparation groups.
Verdict: Supported
Claim: Women aged <35 years had higher clinical pregnancy and live birth rates than women aged ≥35 years.
Evidence type: table
Evidence caption: Table 2: Comparison of reproductive outcomes.
Context: Table 2 shows the clinical outcomes of FET.
Verdict: Supported
Claim: Among young women, the HRT group had higher clinical pregnancy and live birth rates and lower biochemical pregnancy and miscarriage rates than the GnRHa-HRT group, although none of the differences were statistically significant.
Evidence type: table
Evidence caption: Table 2: Comparison of reproductive outcomes.
Context: Table 2 shows the clinical outcomes of FET. Women aged <35 years had higher clinical pregnancy and live birth rates than women aged ≥35 years.
Verdict: Supported
Claim: In the adjusted regression, being male (aPR = 1.05; 95% CI [1.01–1.10]; p = 0.024), recommendation by family and friends (aPR = 1.08; 95% CI [1.04–1.12]; p < 0.001), and recommendation by physicians (aPR = 1.40; 95% CI [1.27–1.55]; p < 0.001) were associated with a higher prevalence of IBV with the booster dose, while age 45 years and older was associated with lower IBV (aPR = 0.89; 95% CI [0.81–0.98]; p = 0.018) ( Table 3 ).
Evidence type: table
Evidence caption: Table 3: Factors associated with the intention to be vaccinated with the COVID-19 booster dose in Peru, July 2022.
Context: In the simple regression, being related to health (PR = 1.10; 95% CI [1.04–1.16]; p < 0.001), having a good perception of its efficacy and protective effect (PR = 3.69; 95% CI [2.57–5.30]; p < 0.001), the recommendation of family and friends (PR = 1.28; 95% CI [1.22–1.34]; p < 0.001), physicians (PR = 1.52; 95% CI [1.38–1.66]; p < 0.001), government health authorities (MINSA) (PR = 1.32; 95% CI [1.24–1.40]; p < 0.001) and politicians (PR = 1.17; 95% CI [1.13–1.21]; p < 0.001) were associated with a higher IBV. Conversely, being aged 45 or older (PR = 0.89; 95% CI [0.81–0.97]; p = 0.011), having children (PR = 0.92; 95% CI [0.87–0.98]; p = 0.006) and being afraid of adverse effects (PR = 0.91; 95% CI [0.87–0.96]; p < 0.001), were associated with a lower prevalence of IBV with the booster dose.
Verdict: Supported
Claim: The addition of an interfragmentary lag screw to the medially positioned plate increased the initial flexural stiffness by 153% and the shear stiffness by 352%, see Table 2 .
Evidence type: table
Evidence caption: Table 2: Comparison of mean values of flexural stiffness, initial flexural stiffness, shear stiffness and maximum load, and their standard deviations (SDs) for different fixation methods.
Verdict: Supported
Claim: The greatest mean maximum load was obtained for the medially positioned plate ( Table 2 ), but the difference between this group and the dorsal LP lag screw and the medial LP lag screw groups was not significant ( p = 0.70 and p = 0.52, respectively).
Evidence type: table
Evidence caption: Table 2: Comparison of mean values of flexural stiffness, initial flexural stiffness, shear stiffness and maximum load, and their standard deviations (SDs) for different fixation methods.
Context: The addition of an interfragmentary lag screw to the medially positioned plate increased the initial flexural stiffness by 153% and the shear stiffness by 352%, see Table 2 . The dorsal plate with the lag screw was the stiffest construct ( Figs. 5A , 5B ). Significant differences in stiffness were observed ( p < 0.05, p -values are given in the Supplemental File ) between all pairs of fixation techniques used in the MTP-1 joint arthrodesis. A greater initial flexural stiffness than the flexural stiffness in the range of 5–200 N was observed especially in the constructs with the interfragmentary lag screw.
Verdict: Supported
Claim: Among SNVs, ETS2 showed the highest mutation frequency (primarily mutation type: missense) ( Figure 4B ).
Evidence type: figure
Evidence caption: Figure 4: Analysis of cellular senescence-related prognostic genes.
(A) Forest plot of prognosis-related genes; (B) waterfall plot of SNVs in the seven prognosis-related genes; (C) Percentage plot of CNVs in the seven prognosis-related genes; (D) The expression of the seven prognosis-related genes expressed in tumor and normal tissues; (E) CDF curve of TCGA cohort; (F) CDF-delta area curves for TCGA cohort. The Delta area curve for consensus clustering indicates the relative change in the area under the CDF curve for each category number, k, relative to k-1. The horizontal axis represents the category number, k, and the vertical axis represents the relative change in area under the CDF curve; (G) Heat map of sample clustering at consensus k = 3; (H) KM curve of the relationship between the prognoses of the three subtypes in TCGA; (I) Heat map of the expression of seven prognosis-related genes among three subtypes in TCGA dataset.

  
Context: The above pathways comprised 253 genes, of which 186 were present in TCGA dataset. Subsequently, a univariate analysis of these 186 genes yielded seven prognosis-related genes, including ETS2, SERPINE1, FOS, SHISA5, IL1A, TP53AIP1, and IGFBP7 ( Figure 4A ). Mutations in these seven genes in TNBC were further examined.
Verdict: Supported
Claim: The prognostic prediction classification efficiency was analyzed separately for 1–5 years with obtained AUC values 0.91, 0.93, 0.74, 0.83 and 0.84, respectively , and the AUC values reached 0.7, indicating good predictive performance.
Evidence type: figure
Evidence caption: Figure 8: Construction and validation of the risk model.
(A) ROC curves for the risk model constructed using four genes from TCGA dataset analysis; (B) KM curves for the risk model based on TCGA dataset; (C) ROC curves for the risk model constructed using four genes for the GSE58812 dataset; (D) KM curves for the risk model based on the GSE58812 dataset.

  
Context: The four genes’ expression levels were utilized to determine the risk score for each sample using the TCGA dataset as the training set. Then, using ROC analysis, the RiskScore prognostic classification was carried out ( Figure 8A ).
Verdict: Supported
Claim: Clinical isolates presented the higher resistance (100%) to the three antibiotics: imipenem, meropenem, and piperacillin/tazobactam.
Evidence type: figure
Evidence caption: Figure 3: Clinical and environmental isolates susceptibility profile.
The percentages of clinical isolates that were resistant, intermediate, or sensitive to each antibiotic. (A) Clinical isolates susceptibility profile, (B) river isolates susceptibility profile. Acronyms: CIP, ciprofloxacin; GEN, gentamycin; SXT, trimethoprim/sulfamethoxazole; AMK, amikacin; FEP, cefepime; MEN, meropenem; IMP, imipenem; TOB, tobramycin; SAM, ampicillin/sulbactam; CAZ, ceftazidime; TZP, piperacillin/tazobactam; R, resistant; I, intermediate; S, sensitive.

  
Verdict: Supported
Claim: Forty-eight percent were susceptible to tobramycin ( Figure 3A ).
Evidence type: figure
Evidence caption: Figure 3: Clinical and environmental isolates susceptibility profile.
The percentages of clinical isolates that were resistant, intermediate, or sensitive to each antibiotic. (A) Clinical isolates susceptibility profile, (B) river isolates susceptibility profile. Acronyms: CIP, ciprofloxacin; GEN, gentamycin; SXT, trimethoprim/sulfamethoxazole; AMK, amikacin; FEP, cefepime; MEN, meropenem; IMP, imipenem; TOB, tobramycin; SAM, ampicillin/sulbactam; CAZ, ceftazidime; TZP, piperacillin/tazobactam; R, resistant; I, intermediate; S, sensitive.

  
Context: Clinical isolates presented the higher resistance (100%) to the three antibiotics: imipenem, meropenem, and piperacillin/tazobactam.
Verdict: Supported
Claim: Nevertheless, the main resistance was to piperacillin/tazobactam (100%).
Evidence type: figure
Evidence caption: Figure 3: Clinical and environmental isolates susceptibility profile.
The percentages of clinical isolates that were resistant, intermediate, or sensitive to each antibiotic. (A) Clinical isolates susceptibility profile, (B) river isolates susceptibility profile. Acronyms: CIP, ciprofloxacin; GEN, gentamycin; SXT, trimethoprim/sulfamethoxazole; AMK, amikacin; FEP, cefepime; MEN, meropenem; IMP, imipenem; TOB, tobramycin; SAM, ampicillin/sulbactam; CAZ, ceftazidime; TZP, piperacillin/tazobactam; R, resistant; I, intermediate; S, sensitive.

  
Context: Clinical isolates presented the higher resistance (100%) to the three antibiotics: imipenem, meropenem, and piperacillin/tazobactam. Forty-eight percent were susceptible to tobramycin ( Figure 3A ). The river isolates displayed an antimicrobial profile that varied between resistant and intermediate to eight antibiotics tested.
Verdict: Supported
Claim: However, under anaerobic culture conditions, NEMM had greater alpha diversity indices of ACE and Chao1 than SHI ( Figure 5A ).
Evidence type: figure
Evidence caption: Figure 5: General bacterial community structure analysis between NEMM and SHI media during aerobic (normoxia) and anaerobic culture.
(A) Alpha diversity was measured with ACE index and Chao1 index. P < 0.05 was considered statistically significant. (B) NMDS was measured with Unweighted UniFrac. Each sample is represented by a dot. (C) Venn diagram displays the number of common and unique characteristics among the groups.

  
Context: To compare NEMM with SHI, which are suitable for cultivating specific bacterial types, we further analyzed 16S rRNA gene high-throughput sequencing data. Alpha diversity indices of ACE and Chao1 showed no significant difference between NEMM and SHI under the normoxia condition.
Verdict: Supported
Claim: Additionally, those in NEMM displayed an increased relative abundance of protein functions linked to defense metabolism, inorganic ion transport and metabolism under anaerobic conditions.
Evidence type: figure
Evidence caption: Figure 8: Function prediction by PICRUSt2.
The differential analysis of COG function (A) and KEGG pathway (B) show the abundance ratio of different functions between groups, whose middle figures show the difference ratio of functional abundance within the 95% confidence interval.

  
Context: To assess the effects of the two media on the predicted gene categories (COGs), we compared the predicted COGs between aNEMM and aSHI, nNEMM and nSHI ( Figure 8A ). NEMM showed more ability in carbohydrate transport and metabolism than SHI medium under both anaerobic conditions and normoxia conditions.
Verdict: Supported
Claim: Cluster analysis found significant differences between the cervical cancer group and the normal group, and the data patterns of five samples in each group have high similarity, proving that some protein levels indeed differ between the two groups ( Figure 1B ).
Evidence type: figure
Evidence caption: Figure 1: Differential expression of the proteins.
(A) A volcano plot is drawn using the protein expression difference multiple and P-value between the two groups of samples, showing the signiﬁcant differences in data between the two groups of samples. Signiﬁcantly up-regulated or down-regulated DEPs are represented in red or green, while proteins with no signiﬁcant change are shown in black. (B) Compared with the control group, hierarchical cluster analysis of DEPs in the cervical cancer group shows that DEPs are up-regulated (orange) or down-regulated (blue). Ctr1~5 are ﬁve biological replicates of the normal group. CC1~5 are ﬁve biological replicates of the cervical cancer group. Each row represents the relative expression of a protein in 10 samples, and each column represents the relative expression of differentially abundant proteins in each experimental group. (P < 0.05, log2 fold change ≥1.0 or ≤−1.0). X-axis: log2 converted difference multiple values; Y-axis: −log10 transformed P-value.

  
Context: In the analysis of significant differences in the quantitative results, we first filter the data within the sample group where at least half of the repeated experimental data are non-null values for differential comparative analysis. Proteins meeting the criteria of an expression difference multiple greater than 1.5 and a P -value less than 0.05 are considered differentially expressed proteins (DEPs). Compared to normal results, there are a total of 562 DEPs in the cervical cancer group, with 340 up-regulated and 222 down-regulated ( Figure 1A ). The top 20 up-regulated and down-regulated DEPs are shown in Table 1 .
Verdict: Supported
Claim: The results are illustrated in Figure 6D , where the top three Sub-cellular locations are cytosol (29.6%), nucleus (26.0%), and extracellular (17.6%).
Evidence type: figure
Evidence caption: Figure 6: Structural domain, transcription factor analysis, and sub-cellular localization analysis.
(A) Enrichment classiﬁcation statistical bubble chart for protein structure domain (top 20). The bubble chart shows that many proteins structure domains were involved in the study, such as guanine nucleotide exchange factor N-terminal, anaphylatoxin-complement system domain, complement_C3_C4_C5, anaphylatoxin-complement system, conserved site RNA recognition motif domain, serpin family, serpin domain, serpin superfamily, and the RNA-binding domain superfamily. Y-axis: structure domain name; X-axis: Rich Factor Value. The circle color represents the −log10 transformed P-value; a deeper color indicates a smaller P-value. The circle size indicates the number of differential proteins contained in this pathway. (B) Enrichment classification statistical bar chart for protein structure domain (Top 20). Y-axis: structure domain name; X-axis: −log10 transformed P-value. The number on the bar represents the Rich Factor value. (C) Top 10 TF family statistical chart; (D) protein subcellular localization distribution chart: Different colors represent different cellular locations, and the percentage indicates the proportion of proteins located there among all differential proteins.

  
Context: Sub-cellular localization refers to the specific location within a cell where a protein or expressed product is found. The main Sub-cellular locations in eukaryotic cells include extracellular space, cytoplasm, cell nucleus, cell membrane, mitochondria, Golgi apparatus, endoplasmic reticulum, peroxisomes, cytoskeleton, nucleoplasm, nuclear matrix, and ribosomes, among others. Understanding the sub-cellular localization of proteins is pivotal for functional protein research. Proteins must be transported to the correct cellular organelle to participate in various life activities and effectively execute their functions. In this study, the software WoLF PSORT is employed for Sub-cellular localization analysis of differential proteins.
Verdict: Supported