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1 models to zero-shot GPT-4 and a second human annotator.
2 Annotator, and cTAKES Fast Dictionary Lookup Annotator.
3 iversity book that was manually marked by an annotator.
4 ences which need to be examined by the human annotator.
5 resent the first automatic coda detector and annotator.
6 t surgery were manually labeled by a trained annotator.
7 eath, which is typically measured by trained annotators.
8 psychological constructs as judged by manual annotators.
9 baseline methods and approach those of human annotators.
10 nscriptomes and compare the results to other annotators.
11 ally distinguishable from real ones by human annotators.
12 rediction using the currently available gene annotators.
13  were tested and manually evaluated by three annotators.
14 inations achieve results close to one of the annotators.
15 cords that can be modified by the NCBI staff annotators.
16 evels of accuracy approaching those of human annotators.
17 ty of laboratory biologists and professional annotators.
18 , and sometimes surpasses, that of the human annotators.
19 ground truth quantifications produced by two annotators.
20  of dataset type, augmentation, or number of annotators.
21 e also compared against additional clinician annotators.
22 e CNN performance was compared to six manual annotators.
23            Here, we present Gaia (Genomic AI Annotator), a sequence annotation platform that enables
24                                     The GSDB Annotator, a multi-platform graphic user interface, is f
25                       Here, we developed NLR-Annotator, a software tool for in silico NLR identificat
26 non-inferior performance to the second human annotator across all four datasets, with an average exac
27 monstrate the universal applicability of NLR-Annotator across diverse plant taxa.
28 ssments comparing their performance to human annotators across multiple dimensions are lacking.
29                                      The SNP Annotator adds traits, ontology terms, effects and inter
30  behind an indicative measure of human inter annotator agreement on the same task.
31                           We report an inter-annotator agreement rate of over 60% for triggers and of
32 provides corpus quality assessment via inter-annotator agreement statistics, and a user-friendly inte
33 us is additional evidence, beyond high inter-annotator agreement, that the quality of the CRAFT corpu
34 re comprehensive interactive graphical tool (Annotator), along with the underlying codebase written i
35 tional Center for Biomedical Ontology (NCBO) Annotator-an ontology-based annotation service-to make i
36 ve and interactive process between the human annotator and a probabilistic named entity tagger.
37 round genomic variants, with built-in SnpEff annotator and customizable window sizes.
38 t our approach, CAnceR geNe similarity-based Annotator and Finder (CARNAF), enables detection of pote
39 nalysis Program (HPAP), we develop AnnoSpat (Annotator and Spatial Pattern Finder) that uses neural n
40 ts accuracy is comparable to that of a human annotator and that it is efficient in various setups and
41 strate considerable agreements between human annotators and ANMAF on detection, segmentation, and the
42 is to support the work of expert manual gene annotators and automated gene annotation pipelines.
43 ojects, and should be useful in training new annotators and consumers in the production of GO annotat
44 ports three levels of users: public viewers, annotators and curators.
45 lass-conditional reliabilities of individual annotators and demonstrate that Gaussian-process classif
46                  The study involved 33 human annotators and eight LLM variants assessing 100 curated
47                         Using multiple human annotators and ensembles of trained networks can improve
48 cation, we compare results with expert human annotators and find comparable performance.
49 re created by a growing community of skilled annotators and provide an introduction to linear motif f
50 ed randomized area tracings for AI and human annotators and qualitatively assessed them.
51 hree dictionary-based systems (MetaMap, NCBO Annotator, and ConceptMapper) are evaluated on eight bio
52 ep, Concept Mapper, cTAKES Dictionary Lookup Annotator, and cTAKES Fast Dictionary Lookup Annotator.
53 hical client-server interface tool, the GSDB Annotator, and via GIO (GSDB Input/Output) files.
54 owns by comparing annotations among multiple annotators as well as overlapping field-annotated crowns
55 s, manually assigned to documents by trained annotators, as clues to select important text segments f
56                                      Trained annotators assessed images and generated data necessary
57                                     Teams of annotators assessed more than 4000 multimedia posts from
58 man and Vertebrate Annotation (HAVANA) group annotators at the Sanger center are using this to annota
59 ils to meet the 'gold standard' of the human annotator because of the difficult recognition stage.
60  validated model of decision making to model annotator behavior, our technique opens the avenue of pr
61 riptions, gene symbols, Gene Ontology terms, annotator comments and links to National Center for Biot
62 curated training dataset, verified by double annotators, consisting of vascular data from three kidne
63  data, either automatically or through human annotators, creating a large corpus of data written in t
64                        Comparison with other annotators demonstrates that ToxCodAn has better perform
65 e convenient for annotation review and inter-annotator disagreement resolution to improve corpus qual
66                   The Dual Organellar GenoMe Annotator (DOGMA) automates the annotation of organellar
67 hensive pipeline called Extensive de-novo TE Annotator (EDTA) that produces a filtered non-redundant
68 ng can save annotation cost by helping human annotators efficiently and intelligently select which sa
69                                              Annotator enables unified spectrum annotation for bottom
70  of predicting neuroscientific biomarkers of annotators, expanding the scope of what may be learnt ab
71 me-consuming and subject to inter- and intra-annotator experience.
72                   Here, we present the Birth Annotator for Budding Yeast (BABY), an algorithm to dete
73 icle introduces BAKIR (Biologically informed Annotator for KIR locus), a tailored computational tool
74 ceeds that of both crowd workers and trained annotators for all tasks.
75 ne-tuned REBEAN (Read Embedding-Based Enzyme ANnotator) for predicting the enzymatic potential encode
76          Currently, over a hundred community annotators help curate the database.
77  ground truth estimation from multiple human annotators helps to establish objectivity in fluorescent
78   Significant variation was observed between annotators, highlighting bias when manual analysis is pe
79                                          The annotators identified 3528 spans of PHI text within the
80 hin these extensive video recordings, manual annotators identified 7352 video segments containing het
81   GPT-4 was non-inferior to the second human annotator in all datasets except kidney pathology.
82       Their performance is compared to human annotators in analyzing sentiment, political leaning, em
83 anding the scope of what may be learnt about annotators in crowdsourcing tasks.
84 ht priority genes for annotation, and to aid annotators in selecting gene evidence tracks from 91 tis
85 rough the sensitivities and specificities of annotators in the binary label setting).
86  outperform xMSannotator (a state-of-the-art annotator) in terms of both performance and computation
87                         Using this automatic annotator, insights into the characterization of sperm w
88                                          The Annotator integrates all known post-translational modifi
89                         DIYA (Do-It-Yourself Annotator) is a modular and configurable open source pip
90 al annotation, when performed by experienced annotators, is more accurate and complete than automated
91 ntify a core potential failure, finding that annotators label objects differently depending on whethe
92 the drift-diffusion model, as a prior on the annotator labeling process.
93 ations vary in quality between databases and annotators, making assessment of annotation reliability
94                             First, two human annotators manually reviewed a purposeful training sampl
95                            We found that the annotators' object-level agreement significantly increas
96 80% consistency on key attributes with human annotators on SEEDLingS and 84 to 93% consistency on vid
97 el image segmentation is biased by the human annotator or trainer.
98  was used to predict ground truth labels and annotator related parameters.
99 ributions are typically imposed as priors on annotator reliability.
100  displays figures from the full text for the annotator's convenience.
101 schema for entities and relations and select annotator(s) and distribute documents anonymously to pre
102  work, we developed Somatic Binding Sequence Annotator (SBSA) as a full-capacity online tool to annot
103 om muxFM data alone as successfully as human annotators seeing only the muxFM data, and accurately re
104 vations indicate that a rigorous process for annotator selection, along with detailed annotation guid
105                We present Systematic ProtEin AnnotatoR (SPEAR), a lightweight and rapid SARS-CoV-2 va
106 thod, known as ALIGATOR (Association LIst Go AnnoTatOR), successfully detected biological pathways im
107 ourcing involves estimating reliabilities of annotators (such as through the sensitivities and specif
108 n platforms such as MTurk as well as trained annotators, such as research assistants.
109 eComet, a web application for biologists and annotators that facilitates the re-annotation of gene ex
110 d adherence to the valuable input of a human annotator through scribbles on histology images, providi
111     This extension of GO allows gene product annotators to comprehensively capture the genetic progra
112 s estimated by SVGPCR may assist in matching annotators to tasks where they perform well.
113 res access to good genome browsers to enable annotators to visualize and evaluate multiple lines of e
114                                          The annotator tool in PeerGAD is built around a genome brows
115 d and further annotated by a team of trained annotators using a new Curation and Annotation Tool.
116 ability (Cohen's kappa) with a trained human annotator was 0.888.
117 oncordance correlation coefficient for human annotators was 0.862, suggesting excellent agreement.
118 enes in phages is a problem for current gene annotators, we exploit this property by treating a phage
119 d predicted scores with errors comparable to annotators were achieved.
120     Coughs were labelled by multiple trained annotators who listened to the continuous audio recordin
121                           MGD scientists and annotators work cooperatively with the research communit
122                                              Annotators worldwide are currently using ASAP to partici

 
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