HTTP 200 OK
Allow: GET
Content-Type: application/json
Vary: Accept
{
"count": 98235,
"next": "https://eartharxiv.org/api/keywords/?format=api&limit=100&offset=45800",
"previous": "https://eartharxiv.org/api/keywords/?format=api&limit=100&offset=45600",
"results": [
{
"word": "Psychology; Perception; Vision; Eye tracking"
},
{
"word": "Cognitive development; Motor control; Spatial cognition; Knowledge representation; Neural Networks"
},
{
"word": "Cognitive Neuroscience; Spatial cognition; fMRI"
},
{
"word": "Action; Perception; Spatial cognition; Vision; Psychophysics"
},
{
"word": "Cognitive Neuroscience; Cognitive development; Problem Solving; Spatial cognition; fMRI"
},
{
"word": "Linguistics; Music; Cross-linguistic analysis"
},
{
"word": "Psychology; Concepts and categories; Computational Modeling; Computer-based experiment"
},
{
"word": "Cognitive Neuroscience; Psychology; Animal cognition; Cognitive development; Computer-based experiment"
},
{
"word": "Cognitive Neuroscience; Decision making; Memory; Computational Modeling"
},
{
"word": "Cognitive Neuroscience; Psychology; Decision making; Computational neuroscience; Neural Networks"
},
{
"word": "Linguistics; Psychology; Language understanding; Eye tracking"
},
{
"word": "Other; Psychology; Behavioral Science"
},
{
"word": "Psychology; Language learning; Statistical learning"
},
{
"word": "Psychology; Pragmatics; Social cognition"
},
{
"word": "Psychology; Language understanding; Morphology; Semantics"
},
{
"word": "Language learning; Spatial cognition; Syntax; Bayesian modeling; fMRI"
},
{
"word": "Artificial Intelligence; Psychology; Discourse; Natural Language Processing; Predictive Processing; Reading; Semantics; Computer-based experiment; Large Language Models"
},
{
"word": "Psychology; Cognitive development; Decision making; Development; Bayesian modeling; Computational Modeling"
},
{
"word": "Neuroscience; Language Production; Language understanding; Predictive Processing; Electroencephalography (EEG)"
},
{
"word": "Psychology; Behavioral Science; Decision making; Emotion; Learning; Computer-based experiment"
},
{
"word": "Interactive behavior; Social cognition; Agent-based Modeling; Bayesian modeling; Computational Modeling"
},
{
"word": "Psychology; Behavioral Science; Decision making; Mood; Computational Modeling"
},
{
"word": "Artificial Intelligence; Cognitive Neuroscience; Representation; Computational Modeling; Neural Networks"
},
{
"word": "Psychology; Attention; Face Processing; Language development; Multilingualism; Social cognition"
},
{
"word": "Linguistics; Psychology; Language and thought; Pragmatics; Case studies; Corpus studies"
},
{
"word": "Cognitive Neuroscience; Language Production; Language understanding; Perception; Reading; Speech recognition; fMRI"
},
{
"word": "Linguistics; Language Production; Phonology; Corpus studies; Statistics"
},
{
"word": "Computer Science; Psychology; Language and thought; Natural Language Processing; Large Language Models"
},
{
"word": "Attention; Social cognition"
},
{
"word": "Psychology; cognitive neuropsychology; Machine learning; Representation; Sensory Processing; fMRI"
},
{
"word": "Cognitive Neuroscience; Behavioral Science; Embodied Cognition; Emotion; Emotion Disorder; Emotion Perception; Social cognition; Brain Stimulation; Clinical methods; Discourse Analysis; Eye tracking; "
},
{
"word": "Linguistics; Psychology; Machine learning; Natural Language Processing; Speech recognition"
},
{
"word": "Artificial Intelligence; Psychology; Decision making; Human-computer interaction; Machine learning"
},
{
"word": "Artificial Intelligence; Computer Science; Linguistics; Language development; Language learning; Machine learning; Natural Language Processing; Computational Modeling; Large Language Models"
},
{
"word": "Cognitive Neuroscience; Psychology; Cognitive development; Bayesian modeling; fMRI"
},
{
"word": "Libyan Studies"
},
{
"word": "SWANA Studies"
},
{
"word": "bottled water"
},
{
"word": "1-20 µm fraction"
},
{
"word": "herpes simplex virus type 2"
},
{
"word": "Covid-19 Patients"
},
{
"word": "Kurdistan Province."
},
{
"word": " Social life"
},
{
"word": " Employees"
},
{
"word": " Organizations"
},
{
"word": " Job performance."
},
{
"word": "analyzing the clinical data of 72 patients with heat stroke admitted to Chongqing Emergency Medical Center between May 2016 and October 2023. The patients were divided into two groups to implement a c"
},
{
"word": "and the other consisting of those who had survived. The study analyzed the risk factors affecting 30-day mortality"
},
{
"word": "Univariate and multivariate logistic regression analysis were performed to construct a clinical prediction model. The nomogram was drawn to visualize the clinical model. Receiver operating characteris"
},
{
"word": "a decision curve analysis was also performed to evaluate the clinical usefulness of the nomogram.是否改为布莱尔分数 Results: Within a 30-day period"
},
{
"word": "21 patients (29.167%) died. The APACHE II score"
},
{
"word": "the ratio of lactate to albumin (Lac/Alb ratio)"
},
{
"word": "the core temperature at 30 minutes after admission were the independent risk factors for 30-day death in heat stroke patients. The area under the ROC curve for predicting mortality based on the APACHE"
},
{
"word": "P<0.001). The best cut-off value was 29"
},
{
"word": "with a sensitivity of 57.1% and a specificity of 92.2%. Moreover"
},
{
"word": "the area under the ROC curve for predicting mortality based on the Lac/Alb ratio was 0.902 (95% CI 0.830-0.975"
},
{
"word": "P<0.001). The optimal cut-off value was 0.160"
},
{
"word": "with a sensitivity of 90.5% and a specificity of 88.2%. The area under the ROC curve based on the core temperature at 30 minutes after admission was 0.700 (95% CI 0.544-0.855"
},
{
"word": "P=0.008). The optimal cut-off value was determined to be 39.5℃"
},
{
"word": "with a sensitivity of 61.9% and a specificity of 80.4%. Finally"
},
{
"word": "the area under the ROC curve for predicting death due to heat stroke using the combination of these three factors was 0.917 (95% CI 0.851-0.983"
},
{
"word": "P<0.001)"
},
{
"word": "with a sensitivity of 76.2% and a specificity of 92.2%. The calibration curve and decision curve analysis showed that nomogram had better accuracy and potential application value in predicting the pro"
},
{
"word": "Heat stroke"
},
{
"word": "30-Day Mortality"
},
{
"word": " coastal adaptation"
},
{
"word": "N/A (book review)"
},
{
"word": "imagin"
},
{
"word": "picture books"
},
{
"word": " language preservation"
},
{
"word": " Palauan"
},
{
"word": " Midjourney"
},
{
"word": "child literacy"
},
{
"word": "language preservation"
},
{
"word": "AI technology"
},
{
"word": "Disseminated Norwegian Scabies"
},
{
"word": "Neglected Tropical Disease"
},
{
"word": "Sarcoptes scabiei var. hominis"
},
{
"word": "Life-history strategy"
},
{
"word": "tree demography"
},
{
"word": "vital rate"
},
{
"word": "ordinary differential equation"
},
{
"word": "street tree"
},
{
"word": "urban management"
},
{
"word": "paradoxical vocal cord motion; ketamine; case report"
},
{
"word": "environmental modeling"
},
{
"word": "EcoEvoRxiv"
},
{
"word": "Mangroves; Red List of Ecosystems; threats; USA; Mexico; Tamaulipas; Texas; Louisiana; Florida"
},
{
"word": "high-tide flooding"
},
{
"word": "participatory writing"
},
{
"word": "participatory culture"
},
{
"word": "remote teaching"
},
{
"word": "sociocultural learning theory"
},
{
"word": "remote instruction"
},
{
"word": "social and emotional learning (SEL)"
},
{
"word": "course design"
},
{
"word": "international graduate students"
},
{
"word": "parent-centered practices"
},
{
"word": "complex communication needs"
},
{
"word": "Spanish-English bilingual"
}
]
}