cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.kpxure
title: Occurrence Download

description: A dataset containing 208 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_0_GID","value":"ARG","matchCase":false},{"type":"equals","key":"GADM_LEVEL_1_GID","value":"ARG.21_1","matchCase":false},{"type":"equals","key":"GADM_LEVEL_2_GID","value":"ARG.21.5_1","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 208 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060478-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tu82m7
title: Occurrence Download

description: A dataset containing 565 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tremella hypogymniae"
 ]
}

 The dataset includes 565 records from 58 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060479-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/jvh4cj
title: PAN-00182765 - (pseudo-) coin pendant (undetermined)

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00182765&lt;/p&gt;
description: Modified: 2025-11-17T15:52:04+01:00
DOI: 10.15468/dl.77shsg
title: Occurrence Download

description: A dataset containing 3241 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Helianthemum squamatum",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3241 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060480-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tyhnrk
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Trees of Berliin",
 "EventDate is 2025-11-19,2025-12-19"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060481-251120083545085/datasets/export for details.
DOI: 10.6084/m9.figshare.28689210
title: Evaluating the Accuracy and Readability of ChatGPT-4o’s Responses to Patient-Based Questions about Keratoconus

description: This study aimed to evaluate the accuracy and readability of responses generated by ChatGPT-4o, an advanced large language model, to frequently asked patient-centered questions about keratoconus. A cross-sectional, observational study was conducted using ChatGPT-4o to answer 30 potential questions that could be asked by patients with keratoconus. The accuracy of the responses was evaluated by two board-certified ophthalmologists and scored on a scale of 1 to 5. Readability was assessed using the Simple Measure of Gobbledygook (SMOG), Flesch-Kincaid Grade Level (FKGL), and Flesch Reading Ease (FRE) scores. Descriptive, treatment-related, and follow-up-related questions were analyzed, and statistical comparisons between these categories were performed. The mean accuracy score for the responses was 4.48 ± 0.57 on a 5-point Likert scale. The interrater reliability, with an intraclass correlation coefficient of 0.769, indicated a strong level of agreement. Readability scores revealed a SMOG score of 15.49 ± 1.74, an FKGL score of 14.95 ± 1.95, and an FRE score of 27.41 ± 9.71, indicating that a high level of education is required to comprehend the responses. There was no significant difference in accuracy among the different question categories (<i>p</i> = 0.161), but readability varied significantly, with treatment-related questions being the easiest to understand. ChatGPT-4o provides highly accurate responses to patient-centered questions about keratoconus, though the complexity of its language may limit accessibility for the general population. Further development is needed to enhance the readability of AI-generated medical content.
DOI: 10.6084/m9.figshare.28689210.v1
title: Evaluating the Accuracy and Readability of ChatGPT-4o’s Responses to Patient-Based Questions about Keratoconus

description: This study aimed to evaluate the accuracy and readability of responses generated by ChatGPT-4o, an advanced large language model, to frequently asked patient-centered questions about keratoconus. A cross-sectional, observational study was conducted using ChatGPT-4o to answer 30 potential questions that could be asked by patients with keratoconus. The accuracy of the responses was evaluated by two board-certified ophthalmologists and scored on a scale of 1 to 5. Readability was assessed using the Simple Measure of Gobbledygook (SMOG), Flesch-Kincaid Grade Level (FKGL), and Flesch Reading Ease (FRE) scores. Descriptive, treatment-related, and follow-up-related questions were analyzed, and statistical comparisons between these categories were performed. The mean accuracy score for the responses was 4.48 ± 0.57 on a 5-point Likert scale. The interrater reliability, with an intraclass correlation coefficient of 0.769, indicated a strong level of agreement. Readability scores revealed a SMOG score of 15.49 ± 1.74, an FKGL score of 14.95 ± 1.95, and an FRE score of 27.41 ± 9.71, indicating that a high level of education is required to comprehend the responses. There was no significant difference in accuracy among the different question categories (<i>p</i> = 0.161), but readability varied significantly, with treatment-related questions being the easiest to understand. ChatGPT-4o provides highly accurate responses to patient-centered questions about keratoconus, though the complexity of its language may limit accessibility for the general population. Further development is needed to enhance the readability of AI-generated medical content.
DOI: 10.6084/m9.figshare.28375613
title: A Cross-Sectional Study of Demographic Representativeness of Glaucoma Patient Populations in Clinical Trials from 2006 to 2022

description: A Cross-Sectional Study of Demographic Representativeness of Glaucoma Patient Populations in Clinical Trials from 2006 to 2022
DOI: 10.6084/m9.figshare.28375613.v1
title: A Cross-Sectional Study of Demographic Representativeness of Glaucoma Patient Populations in Clinical Trials from 2006 to 2022

description: A Cross-Sectional Study of Demographic Representativeness of Glaucoma Patient Populations in Clinical Trials from 2006 to 2022
DOI: 10.6084/m9.figshare.28776541
title: Duration and Frequency of Lapses in Care Among Patients with Proliferative Diabetic Retinopathy

description: Duration and Frequency of Lapses in Care Among Patients with Proliferative Diabetic Retinopathy
DOI: 10.6084/m9.figshare.28776541.v1
title: Duration and Frequency of Lapses in Care Among Patients with Proliferative Diabetic Retinopathy

description: Duration and Frequency of Lapses in Care Among Patients with Proliferative Diabetic Retinopathy
DOI: 10.6084/m9.figshare.28716210
title: Conversational Guide for Cataract Surgery Complications: A Comparative Study of Surgeons versus Large Language Model-Based Chatbot Generated Instructions for Patient Interaction

description: It is difficult to explain the complications of surgery to patients. Care has to be taken to convey the facts clearly and objectively while expressing concern for their wellbeing. This study compared responses from surgeons with responses from a large language model (LLM)-based chatbot. We presented 10 common scenarios of cataract surgery complications to seven senior surgeons and a chatbot. The responses were graded by two independent graders for comprehension, readability, and complexity of language using previously validated indices. The responses were analyzed for accuracy and completeness. Honesty and empathy were graded for both groups. Scores were averaged and tabulated. The readability scores for the surgeons (10.64) were significantly less complex than the chatbot (12.54) (<i>p</i> &lt; 0.001). The responses from the surgeons were shorter, whereas the chatbot tended to give more detailed answers. The average accuracy and completeness score of chatbot-generated conversations was 2.36 (0.55), which was similar to the surgeons’ score of 2.58 (0.36) (<i>p</i> = 0.164). The responses from the chatbot were more generalized, lacking specific alternative measures. While empathy scores were higher for surgeons (1.81 vs. 1.20, <i>p</i> = 0.041), honesty scores showed no significant difference. The LLM-based chatbot gave a detailed description of the complication but was less specific about the alternative measures. The surgeons had a more in-depth understanding of the situation. The chatbot showed complete honesty but scored less for empathy. With more training using complex real-world scenarios and specialized ophthalmologic data, the chatbots could be used to assist the surgeons in counselling patients for postoperative complications.
DOI: 10.6084/m9.figshare.28716210.v1
title: Conversational Guide for Cataract Surgery Complications: A Comparative Study of Surgeons versus Large Language Model-Based Chatbot Generated Instructions for Patient Interaction

description: It is difficult to explain the complications of surgery to patients. Care has to be taken to convey the facts clearly and objectively while expressing concern for their wellbeing. This study compared responses from surgeons with responses from a large language model (LLM)-based chatbot. We presented 10 common scenarios of cataract surgery complications to seven senior surgeons and a chatbot. The responses were graded by two independent graders for comprehension, readability, and complexity of language using previously validated indices. The responses were analyzed for accuracy and completeness. Honesty and empathy were graded for both groups. Scores were averaged and tabulated. The readability scores for the surgeons (10.64) were significantly less complex than the chatbot (12.54) (<i>p</i> &lt; 0.001). The responses from the surgeons were shorter, whereas the chatbot tended to give more detailed answers. The average accuracy and completeness score of chatbot-generated conversations was 2.36 (0.55), which was similar to the surgeons’ score of 2.58 (0.36) (<i>p</i> = 0.164). The responses from the chatbot were more generalized, lacking specific alternative measures. While empathy scores were higher for surgeons (1.81 vs. 1.20, <i>p</i> = 0.041), honesty scores showed no significant difference. The LLM-based chatbot gave a detailed description of the complication but was less specific about the alternative measures. The surgeons had a more in-depth understanding of the situation. The chatbot showed complete honesty but scored less for empathy. With more training using complex real-world scenarios and specialized ophthalmologic data, the chatbots could be used to assist the surgeons in counselling patients for postoperative complications.
DOI: 10.6084/m9.figshare.28928899
title: Assessing the Readability, Quality, and Visual Accessibility of Patient Education Websites for Laser Refractive Surgery

description: To assess the usability of patient education websites for refractive surgery through an analysis of readability, accountability, subjective quality, and visual accessibility. 50 patient education websites for five refractive surgery modalities were gathered from an incognito Google search and categorized by authorship category: institutional, medical organization, or private practice. Each website was assessed for readability, accountability using the Journal of the American Medical Association (JAMA) benchmark, subjective quality using the DISCERN instrument, and visual accessibility was assessed using the Web Accessibility Evaluation Tool (WAVE). The mean reading grade across all websites was 11.02, exceeding the American Medical Association’s recommended 6th-grade level (<i>p</i> &lt; .001). Institutional websites were the most readable (10.32, <i>p</i> = 0.005) while private practice sites were the least (11.74, <i>p</i> = 0.015). The average JAMA score was 1.52 with no website meeting all four accountability criteria. Websites from medical organizations had significantly higher JAMA scores (1.94, <i>p</i> = 0.049). The average DISCERN score was 51.97 with no differences between authorship categories. Websites had an average of 87.84 visual accessibility violations. Available patient education websites for refractive surgery may suffer from poor readability, quality, and visual accessibility which may limit their usability.
DOI: 10.6084/m9.figshare.28928899.v1
title: Assessing the Readability, Quality, and Visual Accessibility of Patient Education Websites for Laser Refractive Surgery

description: To assess the usability of patient education websites for refractive surgery through an analysis of readability, accountability, subjective quality, and visual accessibility. 50 patient education websites for five refractive surgery modalities were gathered from an incognito Google search and categorized by authorship category: institutional, medical organization, or private practice. Each website was assessed for readability, accountability using the Journal of the American Medical Association (JAMA) benchmark, subjective quality using the DISCERN instrument, and visual accessibility was assessed using the Web Accessibility Evaluation Tool (WAVE). The mean reading grade across all websites was 11.02, exceeding the American Medical Association’s recommended 6th-grade level (<i>p</i> &lt; .001). Institutional websites were the most readable (10.32, <i>p</i> = 0.005) while private practice sites were the least (11.74, <i>p</i> = 0.015). The average JAMA score was 1.52 with no website meeting all four accountability criteria. Websites from medical organizations had significantly higher JAMA scores (1.94, <i>p</i> = 0.049). The average DISCERN score was 51.97 with no differences between authorship categories. Websites had an average of 87.84 visual accessibility violations. Available patient education websites for refractive surgery may suffer from poor readability, quality, and visual accessibility which may limit their usability.
DOI: 10.6084/m9.figshare.30032859
title: Cost, Utilization, and Complications of Corneal Transplant in Affordable Care Act Beneficiaries

description: A knowledge gap persists regarding the utilization of corneal transplant surgery among enrollees in Affordable Care Act (ACA) plans and the factors influencing associated costs and complications post-ACA implementation. This study investigates the demographics, costs, and complications of cornea transplant for patients insured under the ACA from 2015 to 2019. A novel claims dataset of Affordable Care Act (ACA) marketplace plan subscribers was utilized. Multivariable logistic and linear regression models were used to assess demographics, cost, and complication rates of corneal transplant using demographic/clinical data and insurance plan type. Among 26,997,610 enrollees, 0.005% (<i>n</i> = 1266) underwent cornea transplant. About 32.9% (<i>n</i> = 416) of patients experienced a postoperative complication, the most common being corneal transplant failure (15.6%) and infectious keratitis (11.5%). Insurance plan type was not associated with rate of postoperative complications (<i>p</i> = 0.87). Patients with different plan types incurred significantly different out-of-pocket (OOP) cost (<i>p</i> &lt; 0.001), with patients on Silver cost-sharing reduction plans paying the lowest ($4). This study is the first to assess the demographics, costs, and complications of corneal transplant patients within the ACA population. Our findings suggest that patients with higher cost-sharing subsidies experience lower OOP costs and may be more inclined to pursue corneal transplant than those on lower actuarial value plans.
DOI: 10.6084/m9.figshare.30032859.v1
title: Cost, Utilization, and Complications of Corneal Transplant in Affordable Care Act Beneficiaries

description: A knowledge gap persists regarding the utilization of corneal transplant surgery among enrollees in Affordable Care Act (ACA) plans and the factors influencing associated costs and complications post-ACA implementation. This study investigates the demographics, costs, and complications of cornea transplant for patients insured under the ACA from 2015 to 2019. A novel claims dataset of Affordable Care Act (ACA) marketplace plan subscribers was utilized. Multivariable logistic and linear regression models were used to assess demographics, cost, and complication rates of corneal transplant using demographic/clinical data and insurance plan type. Among 26,997,610 enrollees, 0.005% (<i>n</i> = 1266) underwent cornea transplant. About 32.9% (<i>n</i> = 416) of patients experienced a postoperative complication, the most common being corneal transplant failure (15.6%) and infectious keratitis (11.5%). Insurance plan type was not associated with rate of postoperative complications (<i>p</i> = 0.87). Patients with different plan types incurred significantly different out-of-pocket (OOP) cost (<i>p</i> &lt; 0.001), with patients on Silver cost-sharing reduction plans paying the lowest ($4). This study is the first to assess the demographics, costs, and complications of corneal transplant patients within the ACA population. Our findings suggest that patients with higher cost-sharing subsidies experience lower OOP costs and may be more inclined to pursue corneal transplant than those on lower actuarial value plans.
DOI: 10.15468/dl.kex6we
title: Occurrence Download

description: A dataset containing 760 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_0_GID","value":"ARG","matchCase":false},{"type":"equals","key":"GADM_LEVEL_1_GID","value":"ARG.21_1","matchCase":false},{"type":"equals","key":"GADM_LEVEL_2_GID","value":"ARG.21.7_1","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 760 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060482-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vcc993
title: Occurrence Download

description: A dataset containing 2170 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-5.56149 36.47403,-5.61389 36.43309,-5.66021 36.34698,-5.68291 36.23232,-5.67536 36.14321,-5.60333 36.03912,-5.48793 36.07738,-5.49163 36.15063,-5.47255 36.26166,-5.47483 36.34795,-5.4458 36.39762,-5.56149 36.47403))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Columbiformes"
 ]
}

 The dataset includes 2170 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060483-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.30920119
title: Towards societal alignment in the governance of human germline genome editing in the Netherlands

description: Although international consensus exists among scientists that <i>clinical application</i> of human germline genome editing (HGGE) should not occur in the near future, the Dutch parliament is considering significantly expanding HGGE <i>research</i> options. Because HGGE policy determines medical practice and potentially the lives of future generations, it is crucial that public values are safeguarded in pertinent decisions. This study applies the governance ecosystem model and anticipatory governance to provide (i) insight into the HGGE governance ecosystem in the Netherlands, and (ii) recommendations to improve societal alignment. We identify gaps in foresight and engagement activities, and a suboptimal integration of public values. We propose interdisciplinary co-creation of future scenarios, recurrent mixed-method studies, public engagement in funding requirements and transparent policy evaluation to improve societal alignment in HGGE governance. The paper demonstrates the synergy of the governance ecosystem model and anticipatory governance when developing recommendations for societal alignment.
DOI: 10.6084/m9.figshare.30920119.v1
title: Towards societal alignment in the governance of human germline genome editing in the Netherlands

description: Although international consensus exists among scientists that <i>clinical application</i> of human germline genome editing (HGGE) should not occur in the near future, the Dutch parliament is considering significantly expanding HGGE <i>research</i> options. Because HGGE policy determines medical practice and potentially the lives of future generations, it is crucial that public values are safeguarded in pertinent decisions. This study applies the governance ecosystem model and anticipatory governance to provide (i) insight into the HGGE governance ecosystem in the Netherlands, and (ii) recommendations to improve societal alignment. We identify gaps in foresight and engagement activities, and a suboptimal integration of public values. We propose interdisciplinary co-creation of future scenarios, recurrent mixed-method studies, public engagement in funding requirements and transparent policy evaluation to improve societal alignment in HGGE governance. The paper demonstrates the synergy of the governance ecosystem model and anticipatory governance when developing recommendations for societal alignment.
DOI: 10.5281/zenodo.17988167
title: VALIDITY AND RELIABILITY IN MODERN EDUCATIONAL ASSESSMENT: NAVIGATING COMPLEXITIES AND ENSURING EQUITY
DOI: 10.5281/zenodo.17988166
title: VALIDITY AND RELIABILITY IN MODERN EDUCATIONAL ASSESSMENT: NAVIGATING COMPLEXITIES AND ENSURING EQUITY
DOI: 10.15468/dl.qegmn7
title: Occurrence Download

description: A dataset containing 2057904 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tracheophyta",
 "DecimalLatitude is greater than or equal to 35.0",
 "DecimalLatitude is less than or equal to 40.0",
 "DecimalLongitude is greater than or equal to -80.0",
 "DecimalLongitude is less than or equal to -75.0",
 "HasCoordinate is TRUE",
 "HasGeospatialIssue is FALSE"
 ]
}

 The dataset includes 2057904 records from 335 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060458-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.