cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.15604251
title: IODP Expedition 334 Vane shear strength (AVS)

description: Shear strength was measured on section halves using a GEISA automated vane shear (AVS) frame and device controller. The device is suitable for sediment not affected by cementation (i.e., saturated, clay-rich, soft sediment). Shear strength measurements should be considered only approximate, particularly because the influence of pore pressure changes during the undrained experiment cannot be estimated. Report includes vane shear strength at the sample's failure point, maximum torque angle, penetration direction, and rate of vane rotation.
DOI: 10.5281/zenodo.15604252
title: IODP Expedition 334 Vane shear strength (AVS)

description: Shear strength was measured on section halves using a GEISA automated vane shear (AVS) frame and device controller. The device is suitable for sediment not affected by cementation (i.e., saturated, clay-rich, soft sediment). Shear strength measurements should be considered only approximate, particularly because the influence of pore pressure changes during the undrained experiment cannot be estimated. Report includes vane shear strength at the sample's failure point, maximum torque angle, penetration direction, and rate of vane rotation.
DOI: 10.6084/m9.figshare.28700857.v1
title: Asymptotic Behavior of Adversarial Training Estimator under l∞-Perturbation

description: Adversarial training has been proposed to protect machine learning models against adversarial attacks. This paper focuses on adversarial training under l∞-perturbation, which has recently attracted much research attention. The asymptotic behavior of the adversarial training estimator is investigated in the generalized linear model. The results imply that the asymptotic distribution of the adversarial training estimator under l∞-perturbation could put a positive probability mass at 0 when the true parameter is 0, providing a theoretical guarantee of the associated sparsity-recovery ability. Alternatively, a two-step procedure is proposed—adaptive adversarial training, which could further improve the performance of adversarial training under l∞-perturbation. Specifically, the proposed procedure could achieve asymptotic variable-selection consistency and unbiasedness. Numerical experiments are conducted to show the sparsity-recovery ability of adversarial training under l∞-perturbation and to compare the empirical performance between classic adversarial training and adaptive adversarial training.
DOI: 10.6084/m9.figshare.28707156.v1
title: What influences clinical educators’ motivation to teach? A BEME systematic review and framework synthesis based on self-determination theory: BEME Review No. 90

description: Health professions learners are taught by full-time university faculty and by clinicians who teach alongside their clinical practice. This distributed healthcare education model ensures high-quality education but is at risk due to high learner demand, shortage of educators, and economic pressures. Understanding what factors influence clinical educators’ motivation to teach may contribute to the model’s sustainability and educator retention. The present review therefore aimed to systematically search and synthesise factors influencing clinical educators’ motivation to teach. Multiple databases, relevant journals, and the grey literature were searched for studies reporting on clinical educators’ motivation to teach. Data were analysed using a framework synthesis method, based on self-determination theory’s amotivation (e.g. disinterest or unachievable challenges), controlled (e.g. interest in rewards or pressure avoidance), and autonomous (e.g. personal importance and interest) concepts, and nested within a motivation from ‘above’ (i.e. interactions with stakeholders and societal expectations), ‘within’ (i.e. personal beliefs and personality dispositions), and ‘below’ (i.e. perception on learners’ motivation and engagement) framework. Twenty-nine studies were included, published between 1998 and 2022, which reported on educators from diverse disciplines and settings. Educators reported autonomous over controlled motivation to teach, favouring enjoyment, connectedness, professional development, feeling valued for their teaching efforts, and altruistic reasons to teach, over being motivated by incentives and rewards. These results are presented in relation to their origin, as factors influencing motivation ‘above’, ‘within’, and ‘below’. Results from this study have important implications for the development of contextual strategies to optimise learning/work environments and maximise autonomous reasons to teach, enhancing clinical educators’ job satisfaction and retention.
DOI: 10.6084/m9.figshare.28707156
title: What influences clinical educators’ motivation to teach? A BEME systematic review and framework synthesis based on self-determination theory: BEME Review No. 90

description: Health professions learners are taught by full-time university faculty and by clinicians who teach alongside their clinical practice. This distributed healthcare education model ensures high-quality education but is at risk due to high learner demand, shortage of educators, and economic pressures. Understanding what factors influence clinical educators’ motivation to teach may contribute to the model’s sustainability and educator retention. The present review therefore aimed to systematically search and synthesise factors influencing clinical educators’ motivation to teach. Multiple databases, relevant journals, and the grey literature were searched for studies reporting on clinical educators’ motivation to teach. Data were analysed using a framework synthesis method, based on self-determination theory’s amotivation (e.g. disinterest or unachievable challenges), controlled (e.g. interest in rewards or pressure avoidance), and autonomous (e.g. personal importance and interest) concepts, and nested within a motivation from ‘above’ (i.e. interactions with stakeholders and societal expectations), ‘within’ (i.e. personal beliefs and personality dispositions), and ‘below’ (i.e. perception on learners’ motivation and engagement) framework. Twenty-nine studies were included, published between 1998 and 2022, which reported on educators from diverse disciplines and settings. Educators reported autonomous over controlled motivation to teach, favouring enjoyment, connectedness, professional development, feeling valued for their teaching efforts, and altruistic reasons to teach, over being motivated by incentives and rewards. These results are presented in relation to their origin, as factors influencing motivation ‘above’, ‘within’, and ‘below’. Results from this study have important implications for the development of contextual strategies to optimise learning/work environments and maximise autonomous reasons to teach, enhancing clinical educators’ job satisfaction and retention.
DOI: 10.6084/m9.figshare.28734677
title: Likelihood Ratio Tests in Random Graph Models with Increasing Dimensions

description: We explore the Wilks phenomena in two random graph models: the β-model and the Bradley–Terry model. For two increasing dimensional null hypotheses, including a specified null H0:βi=βi0 for i=1,…,r and a homogenous null H0:β1=⋯=βr, we reveal high dimensional Wilks’ phenomena that the normalized log-likelihood ratio statistic, [2{l(β̂)−l(β̂0)}−r]/(2r)1/2, converges in distribution to the standard normal distribution as <i>r</i> goes to infinity. Here, l(β) is the log-likelihood function on the model parameter β=(β1,…,βn)⊤, β̂ is its maximum likelihood estimator (MLE) under the full parameter space, and β̂0 is the restricted MLE under the null parameter space. For the homogenous null with a fixed <i>r</i>, we establish Wilks-type theorems that 2{l(β̂)−l(β̂0)} converges in distribution to a chi-square distribution with r−1 degrees of freedom, as the total number of parameters, <i>n</i>, goes to infinity. When testing the fixed dimensional specified null, we find that its asymptotic null distribution is a chi-square distribution in the β-model. However, unexpectedly, this is not true in the Bradley–Terry model. By developing several novel technical methods for asymptotic expansion, we explore Wilks-type results in a principled manner; these principled methods should be applicable to a class of random graph models beyond the β-model and the Bradley–Terry model. Simulation studies and real network data applications further demonstrate the theoretical results. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.26325152
title: “Who’s watching?”: Exploring patients’ acceptance of having their consultations livestreamed for educational purposes

description: Shortages of clinical placements are an ever-increasing global challenge. Livestreaming clinical experiences to remotely-located learners shows promise in addressing this challenge. However, little is known about the acceptability of livestreamed clinical experiences for patients. Understanding patient views is critical to determine feasibility of this method of delivering clinical experience. This study reports on the experiences of 11 patients who participated in a livestreamed clinical experience in general practices in Yorkshire, United Kingdom. Up to five remotely-located medical students participated in each consultation. Semi-structured interviews were conducted and analysed using thematic analysis. Findings suggest that a livestreamed clinical experience did not impact patients’ experience of their consultation, including willingness to withdraw from the consultation. Smartglasses worn by clinicians did not impede patient-clinician interaction, likely because they did not obstruct eye contact. Patient views varied as to whether or not they preferred to see students on the computer screen during the consultation, raising potential tensions between student learning needs and patient preference. Most patients had no preference as to whether students participated remotely or in person. These findings show promise in terms of patient acceptability but further research evaluating patient perspectives in greater numbers and in other clinical contexts is important.
DOI: 10.6084/m9.figshare.26325152.v1
title: “Who’s watching?”: Exploring patients’ acceptance of having their consultations livestreamed for educational purposes

description: Shortages of clinical placements are an ever-increasing global challenge. Livestreaming clinical experiences to remotely-located learners shows promise in addressing this challenge. However, little is known about the acceptability of livestreamed clinical experiences for patients. Understanding patient views is critical to determine feasibility of this method of delivering clinical experience. This study reports on the experiences of 11 patients who participated in a livestreamed clinical experience in general practices in Yorkshire, United Kingdom. Up to five remotely-located medical students participated in each consultation. Semi-structured interviews were conducted and analysed using thematic analysis. Findings suggest that a livestreamed clinical experience did not impact patients’ experience of their consultation, including willingness to withdraw from the consultation. Smartglasses worn by clinicians did not impede patient-clinician interaction, likely because they did not obstruct eye contact. Patient views varied as to whether or not they preferred to see students on the computer screen during the consultation, raising potential tensions between student learning needs and patient preference. Most patients had no preference as to whether students participated remotely or in person. These findings show promise in terms of patient acceptability but further research evaluating patient perspectives in greater numbers and in other clinical contexts is important.
DOI: 10.6084/m9.figshare.26831711
title: Utility of large language models for creating clinical assessment items

description: To compare student performance, examiner perceptions and cost of GPT-assisted (generative pretrained transformer-assisted) clinical and professional skills assessment (CPSAs) items against items created using standard methods. We conducted a prospective, controlled, double-blinded comparison of CPSA items developed using GPT-assistance with those created through standard methods. Two sets of six practical cases were developed for a formative assessment sat by final year medical students. One clinical case in each set was created with GPT-assistance. Students were assigned to one of the two sets. The results of 239 participants were analysed in the study. There was no statistically significant difference in item difficulty, or discriminative ability between GPT-assisted and standard items. One hundred percent (<i>n</i> = 15) of respondents to an examiner feedback questionnaire felt GPT-assisted cases were appropriately difficult and realistic. GPT-assistance resulted in significant labour cost savings, with a mean reduction of 57% (880 GBP) in labour cost per case when compared to standard case drafting methods. GPT-assistance can create CPSA items of comparable quality with significantly less cost when compared to standard methods. Future studies could evaluate GPT’s ability to create CPSA material in other areas of clinical practice, aiming to validate the generalisability of these findings.
DOI: 10.6084/m9.figshare.26831711.v1
title: Utility of large language models for creating clinical assessment items

description: To compare student performance, examiner perceptions and cost of GPT-assisted (generative pretrained transformer-assisted) clinical and professional skills assessment (CPSAs) items against items created using standard methods. We conducted a prospective, controlled, double-blinded comparison of CPSA items developed using GPT-assistance with those created through standard methods. Two sets of six practical cases were developed for a formative assessment sat by final year medical students. One clinical case in each set was created with GPT-assistance. Students were assigned to one of the two sets. The results of 239 participants were analysed in the study. There was no statistically significant difference in item difficulty, or discriminative ability between GPT-assisted and standard items. One hundred percent (<i>n</i> = 15) of respondents to an examiner feedback questionnaire felt GPT-assisted cases were appropriately difficult and realistic. GPT-assistance resulted in significant labour cost savings, with a mean reduction of 57% (880 GBP) in labour cost per case when compared to standard case drafting methods. GPT-assistance can create CPSA items of comparable quality with significantly less cost when compared to standard methods. Future studies could evaluate GPT’s ability to create CPSA material in other areas of clinical practice, aiming to validate the generalisability of these findings.
DOI: 10.6084/m9.figshare.28734677.v2
title: Likelihood Ratio Tests in Random Graph Models with Increasing Dimensions

description: We explore the Wilks phenomena in two random graph models: the β-model and the Bradley–Terry model. For two increasing dimensional null hypotheses, including a specified null H0:βi=βi0 for i=1,…,r and a homogenous null H0:β1=⋯=βr, we reveal high dimensional Wilks’ phenomena that the normalized log-likelihood ratio statistic, [2{l(β̂)−l(β̂0)}−r]/(2r)1/2, converges in distribution to the standard normal distribution as <i>r</i> goes to infinity. Here, l(β) is the log-likelihood function on the model parameter β=(β1,…,βn)⊤, β̂ is its maximum likelihood estimator (MLE) under the full parameter space, and β̂0 is the restricted MLE under the null parameter space. For the homogenous null with a fixed <i>r</i>, we establish Wilks-type theorems that 2{l(β̂)−l(β̂0)} converges in distribution to a chi-square distribution with r−1 degrees of freedom, as the total number of parameters, <i>n</i>, goes to infinity. When testing the fixed dimensional specified null, we find that its asymptotic null distribution is a chi-square distribution in the β-model. However, unexpectedly, this is not true in the Bradley–Terry model. By developing several novel technical methods for asymptotic expansion, we explore Wilks-type results in a principled manner; these principled methods should be applicable to a class of random graph models beyond the β-model and the Bradley–Terry model. Simulation studies and real network data applications further demonstrate the theoretical results. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.5281/zenodo.15604249
title: IODP Expedition 334 Alkalinity and pH

description: Alkalinity was determined by Gran titration with an autotitrator (Metrohm 794 basic Titrino) using 0.1 M HCl at 20 degrees C. Report includes alkalinity, correction factor (if applicable), and pH.
DOI: 10.5281/zenodo.15604250
title: IODP Expedition 334 Alkalinity and pH

description: Alkalinity was determined by Gran titration with an autotitrator (Metrohm 794 basic Titrino) using 0.1 M HCl at 20 degrees C. Report includes alkalinity, correction factor (if applicable), and pH.
DOI: 10.6084/m9.figshare.28734677.v1
title: Likelihood ratio tests in random graph models with increasing dimensions

description: We explore the Wilks phenomena in two random graph models: the β-model and the Bradley–Terry model. For two increasing dimensional null hypotheses, including a specified null H0:βi=βi0 for i=1,…,r and a homogenous null H0:β1=⋯=βr, we reveal high dimensional Wilks’ phenomena that the normalized log-likelihood ratio statistic, [2{l(β̂)−l(β̂0)}−r]/(2r)1/2, converges in distribution to the standard normal distribution as <i>r</i> goes to infinity. Here, l(β) is the log-likelihood function on the model parameter β=(β1,…,βn)⊤, β̂ is its maximum likelihood estimator (MLE) under the full parameter space, and β̂0 is the restricted MLE under the null parameter space. For the homogenous null with a fixed <i>r</i>, we establish Wilks-type theorems that 2{l(β̂)−l(β̂0)} converges in distribution to a chi-square distribution with r−1 degrees of freedom, as the total number of parameters, <i>n</i>, goes to infinity. When testing the fixed dimensional specified null, we find that its asymptotic null distribution is a chi-square distribution in the β-model. However, unexpectedly, this is not true in the Bradley–Terry model. By developing several novel technical methods for asymptotic expansion, we explore Wilks-type results in a principled manner; these principled methods should be applicable to a class of random graph models beyond the β-model and the Bradley–Terry model. Simulation studies and real network data applications further demonstrate the theoretical results.
DOI: 10.18112/openneuro.ds004103.v1.0.2
title: Collaborations and deceptions in strategic interactions revealed by hyperscanning fMRI
DOI: 10.15468/dl.k6bxkj
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pseudobarbus quathlambae (Barnard, 1938)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((35.6306 -23.844,35.6007 -23.8125,35.6007 -24.0157,35.6306 -23.844))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025551-250525065834625/datasets/export for details.
DOI: 10.5281/zenodo.15604320
title: IODP Expedition 334 Formation temperature

description: Formation temperature was measured by the advanced piston corer temperature tool (APCT-3), Sediment Temperature Tool (SET), or sediment temperature pressure tool (SETP) and reduced to in situ temperature and (for SETP) pressure estimates. These data are compiled per instrument run and assigned to a core (the core cut with the APCT-3 cutting shoe or the core following the SET deployment).
DOI: 10.5281/zenodo.15604321
title: IODP Expedition 334 Formation temperature

description: Formation temperature was measured by the advanced piston corer temperature tool (APCT-3), Sediment Temperature Tool (SET), or sediment temperature pressure tool (SETP) and reduced to in situ temperature and (for SETP) pressure estimates. These data are compiled per instrument run and assigned to a core (the core cut with the APCT-3 cutting shoe or the core following the SET deployment).
DOI: 10.5281/zenodo.15604316
title: IODP Expedition 334 Visual core description

description: Descriptions of samples, generally at the section half and smear slide or thin section scale, were performed by shipboard scientists and recorded in the JRSO description software. Descriptive data for both macroscopic and microscopic examination were collected in a Microscoft Excel workbook by hole. A zip file of the entire expedition's observations is also available.
DOI: 10.5281/zenodo.15604317
title: IODP Expedition 334 Visual core description

description: Descriptions of samples, generally at the section half and smear slide or thin section scale, were performed by shipboard scientists and recorded in the JRSO description software. Descriptive data for both macroscopic and microscopic examination were collected in a Microscoft Excel workbook by hole. A zip file of the entire expedition's observations is also available.
DOI: 10.15468/dl.ttewsy
title: Occurrence Download

description: A dataset containing 5993 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Material sample)"
 ]
 }
 },
 "TaxonKey is Mops Lesson, 1842",
 "Continent is one of (Africa)",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 5993 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025550-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15604314
title: IODP Expedition 334 Inorganic carbon (coulometer)

description: Inorganic carbon (carbonate) is determined by coulometry, which uses a photodetection cell to measure carbon dioxide evolved during sample acidification. Report includes percent inorganic carbon and calcium carbonate.
DOI: 10.5281/zenodo.15604315
title: IODP Expedition 334 Inorganic carbon (coulometer)

description: Inorganic carbon (carbonate) is determined by coulometry, which uses a photodetection cell to measure carbon dioxide evolved during sample acidification. Report includes percent inorganic carbon and calcium carbonate.
DOI: 10.15468/dl.r5g3bw
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Argentina",
 "OccurrenceStatus is Present",
 "TaxonKey is Thelypteris patens var. dissimilis (Schrad.) A.R.Sm."
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025552-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.