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433
datasets available to search
ShareScore release 0.9.0
Dataset results
433 results for “readiness”
PK Study on Ready-to-Use Injection (VSLI-RTU) 1 Vial & 3 Vial Formulation Marqibo® in Hematological Malignant Patients
ClinicalTrials.gov study NCT04243434. IPD Sharing: NO. Countries: 0. Publications: 0.
School Readiness in Children with Type 1 Diabetes
ClinicalTrials.gov study NCT06673251. IPD Sharing: NO. Countries: 0. Publications: 0.
Safety of a Ready to Drink Supplement
ClinicalTrials.gov study NCT03032549. IPD Sharing: NO. Countries: 0. Publications: 0.
Evaluation of Neurological Status and School Readiness in Preterm Preschoolers
ClinicalTrials.gov study NCT03081624. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
A Randomized Clinical Trial Comparing Executive Function and Language Skills Training on School Readiness in Preschool Children
ClinicalTrials.gov study NCT02807831. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Evaluation of the Readiness Supportive Leadership Training - National Guard
ClinicalTrials.gov study NCT07203170. IPD Sharing: YES. Countries: 0. Publications: 0.
Computer-Based Program to Facilitate Readiness and Motivation for Smoking Cessation
ClinicalTrials.gov study NCT01326234. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Non-Stage-Matched Intervention to Enhance High School Female Students' Readiness to Engage in Regular Physical Exercise
ClinicalTrials.gov study NCT05938777. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
Enhancing Operational Readiness With Digital Self-Managed Cognitive Behavioral Therapy for Insomnia (CBTI)
ClinicalTrials.gov study NCT07335276. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
Basal level of ATF4 promotes T cell readiness for activation-induced proliferation [RNA-seq]
GEO Series GSE288143. Mus musculus. 14 samples. Type: Expression profiling by high throughput sequencing.
TrustMus benchmark: The Role of Large Language Models in Musicology: Are We Ready to Trust the Machines?
<p>TrustMus is an initial, rigorously validated benchmark designed to assess the accuracy and reliability of large language models (LLMs) in the domain of musicology. This dataset includes a collection of 400 human-validated multiple-choice questions, categorized into four thematic areas: People (Ppl), Instruments and Technology (I&T), Genres, Forms, and Theory (Thr), and Culture and History (C&H).</p> <p>The questions are derived from <em>The Grove Dictionary Online</em> using a semi-automated methodology. The process involves generating initial questions with a fine-tuned retrieval-augmented generation (RAG) model, filtering them through a series of automated checks, and finally validating them through expert human annotation. TrustMus is introduced in an initial paper, providing a critical resource for researchers and developers aiming to evaluate and improve LLM performance in this specialized field of musicology.</p> <p>This benchmark is discussed in the paper : </p> <p><strong>BibTeX Citation:</strong></p> <div> <div><code>@inproceedings{ramoneda2024trustmus,</code><br><code> title={The Role of Large Language Models in Musicology: Are We Ready to Trust the Machines?},</code><br><code> author={Ramoneda, Pedro and Parada-Cabaleiro, Emilia and Weck, Benno and Serra, Xavier},</code><br><code> booktitle={Proceedings of the 3rd Workshop on NLP for Music and Audio (NLP4MusA)},</code><br><code> year={2024},</code><br><code> month={November},</code><br><code> address={San Francisco, USA},</code><br><code> organization={Co-located with ISMIR'2024}</code><br><code>}</code><br><br> <div> </div> </div> </div>
Replication Package for "On Large Language Models in Mission-Critical IT Governance: Are We Ready Yet?"
<h1>Replication Package for "On Large Language Models in Mission-Critical IT Governance: Are We Ready Yet?"</h1> <h2>Authors</h2> <p>Matteo Esposito, University of Oulu, Finland Francesco Palagiano, Multitel di Lerede Alessandro & C. s.a.s. Valentina Lenarduzzi, University of Oulu, Finland Davide Taibi, University of Oulu, Finland</p> <h2>Content Overview</h2> <p>This replication package contains the following materials:</p> <ul> <li>Data: RAW Questionnaire dataset.</li> <li>Contact Information</li> </ul> <p>For any issues, questions, or further assistance, please do not hesitate to contact the paper's authors. We are here to help!</p>
Database article Developing Sustainable Career Paths for Preuniversity Teachers. An Empirical Analysis of Central Dimensions of Job Readiness
<p>The quality of teacher training is highly likely to influence the quality of learning outcomes. In this view, the present paper aimed to develop a pre-service teachers’ job readiness model integrating individual variables associated with teacher professionalism. The study followed an exploratory cross-sectional research design. A sample of 312 Romanian pre-service STEM (Science, Technology, Engineering, and Mathematics) teachers was selected based on availability criteria. A pre-tested self-administered questionnaire using a 5-point Likert scale was applied during the data collection process. Data analysis was based on a combination of descriptive and inferential statistics, a blending factor analysis and structural equations modeling. A conceptual model of teaching readiness from the teacher professionalism perspective was developed and tested using empirical data. The results suggest that professional knowledge, professional practice, professional engagement and self-management could be considered central dimensions of teacher professionalism, being highly relevant in assessing pre-service teacher job readiness. Moreover, professional knowledge has a strong and positive influence on teaching practice and professional engagement. In relation to the professional knowledge latent variable, the ability to conduct didactic transposition is the most influential. Following the same line of analysis, the most significant vectors of the professional practice variable were found to be the ability to design effective evaluation tools and to analyze and interpret learning outcomes. The research revealed the presence of vulnerable or sensitive areas of teacher training that could be a result of curriculum design. With respect to managing disruptive behaviours, the customization of learning and emotional self-regulation are considered weak areas of teaching readiness. The results could be useful for policymakers and teacher training practitioners in order to improve overall job readiness and teacher professionalism.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.