Many models in natural language processing define probabilistic distributions over linguistic structures. We argue that (1) the quality of a model' s posterior distribution can and should be directly evaluated, as to whether probabilities correspond to empirical frequencies, and (2) NLP uncertainty can be projected not only to pipeline components, but also to exploratory data analysis, telling a user when to trust and not trust the NLP analysis. We present a method to analyze calibration, and apply it to compare the miscalibration of several commonly used models. We also contribute a coreference sampling algorithm that can create confidence intervals for a political event extraction task.
Oral argument is the most public and visible part of the U.S. Supreme Court’s decision-making process. Yet what if some advocates are treated differently be- fore the Court solely because of aspects of their identity? In this work, we leverage a causal inference framework to quantify the effect of an advocate’s gender on interruptions of advocates at both the Court-level and the justice-level. Exam- ining nearly four decades of U.S. Supreme Court oral argument transcript data, we identify a clear and consistent gender effect that dwarfs other influences on justice interruption behavior, with female advocates interrupted more frequently than male advocates.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Automated event extraction in social science applications often requires corpus-level evaluations: for example, aggregating text predictions across metadata and unbiased estimates of recall.We combine corpus-level evaluation requirements with a real-world, social science setting and introduce the INDIAPO-LICEEVENTS corpus-all 21,391 sentences from 1,257 English-language Times of India articles about events in the state of Gujarat during March 2002.Our trained annotators read and label every document for mentions of police activity events, allowing for unbiased recall evaluations.In contrast to other datasets with structured event representations, we gather annotations by posing natural questions, and evaluate off-the-shelf models for three different tasks: sentence classification, document ranking, and temporal aggregation of target events.We present baseline results from zero-shot BERT-based models fine-tuned on natural language inference and passage retrieval tasks.Our novel corpus-level evaluations and annotation approach can guide creation of similar social-science-oriented resources in the future.
Abstract Background Acute appendicitis is the most common surgical emergency in children. Eighty percent of paediatric appendicectomies are performed by adult general surgeons on an annual basis. The remaining 20% are performed at Children’s Health Ireland (CHI) centres. Occasionally patients are transferred from Non-Specialist Paediatric Surgical Centres (NSPSC) for specialised pre-operative or post-operative care. Aim To assess the rates of and characterise appendicitis-related referrals to CHI at Crumlin from NSPSC. Methods A retrospective review of all appendicitis-related transfers to CHI at Crumlin between January 2020 and December 2021 was performed. Data relating to indications for transfer, referring hospital level, patient demographics, management, type of surgery, length of stay (LOS), and radiological studies were collected and analysed. Results Seventy-two patients were transferred to CHI at Crumlin over the 2-year period. A total of 60.9% were male, mean age 9 ± 4.3 years, mean LOS 6.0 ± 2.2 days (range 1–30 days). Nineteen percent were under 5 years of age. Seventy-three percent were transferred from level 4 centres. Ninety-seven percent were transferred pre-operatively, 25% of those transferred pre-operatively had imaging in CHI confirming appendicitis. Fifty-five percent (40/72) of patients had pre-operative imaging performed. A total of 37.5% (15/40) confirmed complicated appendicitis. Twenty percent (8/40) underwent both ultrasound and computerised tomography (CT) at the referring centre. A total of 2.7% (2/72) were transferred with known co-morbidities. Ninety-two percent (66/72) underwent appendicectomy. Eight percent (6/72) were managed non-operatively (NOM) — 2 failed NOM, 2 underwent interval appendicectomy. Of those managed operatively, 76% (50/66) underwent laparoscopic appendicectomy, and 24% (16/66) were performed open. Conclusion The majority of paediatric appendicectomies are performed at Non-Specialist Paediatric Surgical Centres. It is vital to maintain this working relationship so that specialist paediatric centres are available to provide care to complex paediatric patients.
The search for peptidases in brain tissues which may be involved in the inactivation of neuropeptides has been strongly influenced by our knowledge of the inactivation of the cholinergic neurotransmitter acetylcholine by acetylcholinesterase in the vicinity of the synaptic junction. The search for peptidases which may be physiologically significant participants in the termination of neuropeptide activity has been influenced by the possibility that they may be acting as neurotransmitters at synapses and by knowledge of the enzymic inactivation of some classical transmitters such as acetylcholine. One of the more striking differences between the results obtained with whole animal experiment and those obtained with either membrane enriched particulate fractions or with cultured spinal cord cells concerns the nature of the enzyme converting angiotensin II to angiotensin III. A different picture of angiotensin II metabolism emerged from a study on the inactivation of this peptide by cultured mouse spinal cord cells.
In this paper we propose modifications to the neural network framework, AutoVC for the task of singing technique conversion. This includes utilising a pretrained singing technique encoder which extracts technique information, upon which a decoder is conditioned during training. By swapping out a source singer's technique information for that of the target's during conversion, the input spectrogram is reconstructed with the target's technique. We document the beneficial effects of omitting the latent loss, the importance of sequential training, and our process for fine-tuning the bottleneck. We also conducted a listening study where participants rate the specificity of technique-converted voices as well as their naturalness. From this we are able to conclude how effective the technique conversions are and how different conditions affect them, while assessing the model's ability to reconstruct its input data.