Keck Interferometer Nuller Data Reduction and On-Sky Performance

We describe the Keck Interferometer nuller theory of operation, data reduction, and on-sky performance, particularly as it applies to the nuller exozodiacal dust key science program that was carried out between 2008 February and 2009 January. We review the nuller implementation, including the detailed phasor processing involved in implementing the null-peak mode used for science data and the sequencing used for science observing. We then describe the Level 1 reduction to convert the instrument telemetry streams to raw null leakages, and the Level 2 reduction to provide calibrated null leakages. The Level 1 reduction uses conservative, primarily linear processing, implemented consistently for science and calibrator stars. The Level 2 processing is more flexible, and uses diameters for the calibrator stars measured contemporaneously with the interferometer’s K-band cophasing system in order to provide the requisite accuracy. Using the key science data set of 462 total scans, we assess the instrument performance for sensitivity and systematic error. At 2.0 Jy we achieve a photometrically-limited null leakage uncertainty of 0.25% rms per 10 minutes of integration time in our broadband channel. From analysis of the Level 2 reductions, we estimate a systematic noise floor for bright stars of ~0.2% rms null leakage uncertainty per observing cluster in the broadband channel. A similar analysis is performed for the narrowband channels. We also provide additional information needed for science reduction, including details on the instrument beam pattern and the basic astrophysical response of the system, and references to the data reduction and modeling tools

The dusty AGB star RS CrB: first mid-infrared interferometric observations with the Keck Telescopes

We report interferometric observations of the semi-regular variable star RS CrB, a red giant with strong silicate emission features. The data were among the first long baseline mid-infrared stellar fringes obtained between the Keck telescopes, using parts of the new nulling beam combiner. The light was dispersed by a low-resolution spectrometer, allowing simultaneous measurement of the source visibility and intensity spectra from 8 to 12 microns. The interferometric observations allow a non-ambiguous determination of the dust shell spatial scale and relative flux contribution. Using a simple spherically-symmetric model, in which a geometrically thin shell surrounds the stellar photosphere, we find that ~30% to ~70% of the overall mid-infrared flux - depending on the wavelength - originates from 7-8 stellar radii. The derived shell opacity profile shows a broad peak around 11 microns (tau ~ 0.06), characteristic of Mg-rich silicate dust particles.Comment: Accepted for publication in ApJ Letter

Toward patient-tailored summarization of lung cancer literature*

As the volume of biomedical literature increases, it can be challenging for clinicians to stay up-to-date. Graphical summarization systems help by condensing knowledge into networks of entities and relations. However, existing systems present relations out of context, ignoring key details such as study population. To better support precision medicine, summarization systems should include such information to contextualize and tailor results to individual patients.This paper introduces “contextualized semantic maps” for patient-tailored graphical summarization of published literature. These efforts are demonstrated in the domain of driver mutations in non-small cell lung cancer (NSCLC). A representation for relations and study population context in NSCLC was developed. An annotated gold standard for this representation was created from a set of 135 abstracts; F1-score annotator agreement was 0.78 for context and 0.68 for relations. Visualizing the contextualized relations demonstrated that context facilitates the discovery of key findings that are relevant to patient-oriented queries

Toward patient-tailored summarization of lung cancer literature*

As the volume of biomedical literature increases, it can be challenging for clinicians to stay up-to-date. Graphical summarization systems help by condensing knowledge into networks of entities and relations. However, existing systems present relations out of context, ignoring key details such as study population. To better support precision medicine, summarization systems should include such information to contextualize and tailor results to individual patients.This paper introduces “contextualized semantic maps” for patient-tailored graphical summarization of published literature. These efforts are demonstrated in the domain of driver mutations in non-small cell lung cancer (NSCLC). A representation for relations and study population context in NSCLC was developed. An annotated gold standard for this representation was created from a set of 135 abstracts; F1-score annotator agreement was 0.78 for context and 0.68 for relations. Visualizing the contextualized relations demonstrated that context facilitates the discovery of key findings that are relevant to patient-oriented queries

Evaluating Casama: Contextualized semantic maps for summarization of lung cancer studies

OBJECTIVEIt is crucial for clinicians to stay up to date on current literature in order to apply recent evidence to clinical decision making. Automatic summarization systems can help clinicians quickly view an aggregated summary of literature on a topic. Casama, a representation and summarization system based on “contextualized semantic maps,” captures the findings of biomedical studies as well as the contexts associated with patient population and study design. This paper presents a user-oriented evaluation of Casama in comparison to a context-free representation, SemRep.MATERIALS AND METHODSThe effectiveness of the representation was evaluated by presenting users with manually annotated Casama and SemRep summaries of ten articles on driver mutations in cancer. Automatic annotations were evaluated on a collection of articles on EGFR mutation in lung cancer. Seven users completed a questionnaire rating the summarization quality for various topics and applications.RESULTSCasama had higher median scores than SemRep for the majority of the topics (p ≤ 0.00032), all of the applications (p ≤ 0.00089), and in overall summarization quality (p ≤ 1.5e-05). Casama’s manual annotations outperformed Casama’s automatic annotations (p = 0.00061).DISCUSSIONCasama performed particularly well in the representation of strength of evidence, which was highly rated both quantitatively and qualitatively. Users noted that Casama’s less granular, more targeted representation improved usability compared to SemRep.CONCLUSIONThis evaluation demonstrated the benefits of a contextualized representation for summarizing biomedical literature on cancer. Iteration on specific areas of Casama’s representation, further development of its algorithms, and a clinically-oriented evaluation are warranted

FACTS-IR: Fairness, Accountability, Confidentiality, Transparency, and Safety in Information Retrieval

Contains fulltext : 221217.pdf (publisher's version ) (Open Access

FACTS-IR: Fairness, Accountability, Confidentiality, Transparency, and Safety in Information Retrieval

Contains fulltext : 221217.pdf (publisher's version ) (Open Access