Update README.md

README.md

@@ -1,11 +1,20 @@
 ---
 widget:
-- text: " Polygenic risk scores (PRS) describe individual risks for specific diseases based on genetic information from multiple loci. Previous studies suggest that PRS may predict differences in the physiological activation of individuals with agoraphobia. In this study, we examined whether the possibility to predict affected individuals’ heart rate by their PRS depends on the type of exposure trial. We postulated that PRS would predict heart rate within in-vivo as well as in-virtuo trials. Data were analyzed from 132 individuals diagnosed with agoraphobia who underwent either in-vivo (N = 63) or in-virtuo (N = 69) exposure. As assumed, heart rate was significantly predicted by PRS in both trial types. The results of this study suggest that PRS not only provide useful diagnostic information for an individual’s risk of agoraphobia, but that their usefulness in predicting physiological reactions is stable across different exposure settings."
-  example_title: "Ex1: PRS"
-- text: " According to the Socioeconomic Adaptation Theory of Rehabilitation (SAToR), individuals with higher socioeconomic status (SES) tend to benefit more from psychiatric rehabilitation than individuals with lower SES. In line with the SAToR, we hypothesized that higher SES is associated with a greater reduction in symptom severity in patients with schizophrenia. We conducted an observational study over the course of a 12-month rehabilitation program, encompassing 146 participants with schizophrenia who were newly admitted to a psychiatric rehabilitation clinic. A longitudinal multilevel model was computed to predict rates of change in symptom severity. The average rate of symptom change was 0.6 SD from baseline to 6-month follow-up. Contrary to our hypothesis, symptom change was not significantly predicted by SES. This finding suggests that contrary to the SAToR, individuals with higher socioeconomic status (SES) likely do not benefit more from rehabilitation of schizophrenia than individuals with lower SES."
-  example_title: "Ex2: SES"
-- text: " There is growing evidence of deficits in defensive reactivity (indexed by the startle blink reflex) in individuals diagnosed with antisocial personality disorder (ASPD). However, to date, no study has examined the role of defensive reactivity in the quality of life (QoL) of individuals with ASPD. In the current study, we therefore explored whether the startle blink reflex is negatively associated with QoL in 143 individuals diagnosed with ASPD. Defensive reactivity was measured using a fear-potentiated startle reflex test. To assess QoL, participants completed the Short Form (36) Health Survey (SF-36). Startle blink reflex potentiation deficits during aversive picture viewing were common in the sample (62.3%). Blink reflex potentiation was negatively and significantly associated with QoL. In sum, these findings provide clear evidence that deficits in defensive reactivity are linked to poor QoL in ASPD."
-  example_title: "Ex3: SES"
+- text: ' Polygenic risk scores (PRS) describe individual risks for specific diseases based on genetic information from multiple loci. Previous studies suggest that PRS may predict differences in the physiological activation of individuals with agoraphobia. In this study, we examined whether the possibility to predict affected individuals’ heart rate by their PRS depends on the type of exposure trial. We postulated that PRS would predict heart rate within in-vivo as well as in-virtuo trials. Data were analyzed from 132 individuals diagnosed with agoraphobia who underwent either in-vivo (N = 63) or in-virtuo (N = 69) exposure. As assumed, heart rate was significantly predicted by PRS in both trial types. The results of this study suggest that PRS not only provide useful diagnostic information for an individual’s risk of agoraphobia, but that their usefulness in predicting physiological reactions is stable across different exposure settings.'
+  example_title: 'Ex1: PRS'
+- text: ' According to the Socioeconomic Adaptation Theory of Rehabilitation (SAToR), individuals with higher socioeconomic status (SES) tend to benefit more from psychiatric rehabilitation than individuals with lower SES. In line with the SAToR, we hypothesized that higher SES is associated with a greater reduction in symptom severity in patients with schizophrenia. We conducted an observational study over the course of a 12-month rehabilitation program, encompassing 146 participants with schizophrenia who were newly admitted to a psychiatric rehabilitation clinic. A longitudinal multilevel model was computed to predict rates of change in symptom severity. The average rate of symptom change was 0.6 SD from baseline to 6-month follow-up. Contrary to our hypothesis, symptom change was not significantly predicted by SES. This finding suggests that contrary to the SAToR, individuals with higher socioeconomic status (SES) likely do not benefit more from rehabilitation of schizophrenia than individuals with lower SES.'
+  example_title: 'Ex2: SES'
+- text: ' There is growing evidence of deficits in defensive reactivity (indexed by the startle blink reflex) in individuals diagnosed with antisocial personality disorder (ASPD). However, to date, no study has examined the role of defensive reactivity in the quality of life (QoL) of individuals with ASPD. In the current study, we therefore explored whether the startle blink reflex is negatively associated with QoL in 143 individuals diagnosed with ASPD. Defensive reactivity was measured using a fear-potentiated startle reflex test. To assess QoL, participants completed the Short Form (36) Health Survey (SF-36). Startle blink reflex potentiation deficits during aversive picture viewing were common in the sample (62.3%). Blink reflex potentiation was negatively and significantly associated with QoL. In sum, these findings provide clear evidence that deficits in defensive reactivity are linked to poor QoL in ASPD.'
+  example_title: 'Ex3: SES'
+pipeline_tag: text-classification
+tags:
+- metascience
+- psychology
+- psychotherapy
+- publicationbias
+- openscience
+- abstracts
+- science
 ---
 
 ## Model
@@ -29,7 +38,6 @@ from transformers import AutoTokenizer, Trainer, AutoModelForSequenceClassificat
 tokenizer = AutoTokenizer.from_pretrained('allenai/scibert_scivocab_uncased')
 
 ## 2. Apply preprocess function to data
-## Make sure your text column is named 'text'. Otherwise replace 'text' with the name of your text column.
 def preprocess_function(examples):
     return tokenizer(examples["text"],
                      truncation=True,