Baseline patient characteristics across neutralizing monoclonal antibody trials. by Elizabeth S. Munroe (21568166)

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Quantitative antibody and antigen responses to nMAb vs placebo day 1-90: Pooled analysis of neutralizing monoclonal antibodies. by Elizabeth S. Munroe (21568166)

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Longitudinal antibody and antigen responses to treatment vs placebo day 1–90 for neutralizing monoclonal antibodies, among patients alive and with day 90 antibody and antigen measu... by Elizabeth S. Munroe (21568166)

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Antibody and antigen responses to nMAb vs placebo day 1–90 for Amubarvimab/ Romlusevimab. by Elizabeth S. Munroe (21568166)

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Antibody and antigen responses to Ensovibep vs placebo day 1–90. by Elizabeth S. Munroe (21568166)

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Antibody and antigen responses to nMAb vs placebo day 1–90 for Tixagevimab/ Cilgavimab. by Elizabeth S. Munroe (21568166)

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Study Flow Diagram. by Elizabeth S. Munroe (21568166)

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Antibody and antigen responses to nMAb vs placebo day 1–90 for Bamlanivimab. by Elizabeth S. Munroe (21568166)

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Antibody and antigen responses to Lufotrelvir vs placebo day 1–90. by Elizabeth S. Munroe (21568166)

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Antibody and antigen responses to nMAb vs placebo day 1–90 for Sotrovimab. by Elizabeth S. Munroe (21568166)

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Antibody and antigen responses by baseline anti-spike neutralizing response assay positivity. by Elizabeth S. Munroe (21568166)

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Longitudinal antibody and antigen responses to treatment vs placebo day 1–90 for nMAbs, among patients alive and with day 90 antibody and antigen measures (Sensitivity Analysis). by Elizabeth S. Munroe (21568166)

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Long-term anti-nucleocapsid response by baseline patient characteristics. by Elizabeth S. Munroe (21568166)

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Antibody and antigen responses after treatment with nMAb vs placebo, day 1-90 (pooled nMAb treatments). by Elizabeth S. Munroe (21568166)

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Overview of the six original ACTIV-3/TICO trials. by Elizabeth S. Munroe (21568166)

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Line graph showing the increase or decrease in the average number of bee swarms caught over the past three years (Mean  by Beatrice T. Nganso (4114768)

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ECoG timescales decrease during spatial attention. by Isabel Raposo (21615517)

“…Bottom: timescales significantly decrease during covert attention relative to the attend-out condition (two locations: <i>p</i> = 0.0244; four locations: <i>p</i> < 0.0001; mean ± SEM; whiskers indicate maximum and minimum; dots correspond to individual electrodes). …”

Penalty conversions yield large practical decreases, but robustness and generalizability of result are limited by data quality and sample selection. by Ryan J. Treves (13527735)

Data Sheet 1_Emotional prompting amplifies disinformation generation in AI large language models.docx by Rasita Vinay (21006911)

“…Introduction<p>The emergence of artificial intelligence (AI) large language models (LLMs), which can produce text that closely resembles human-written content, presents both opportunities and risks. …”

Feasibility of AI-powered assessment scoring: Can large language models replace human raters? by Michael Jaworski III (22156096)

“…<p><b>Objective:</b> To assess the feasibility, accuracy, and reliability of using ChatGPT-4.5 (early-access), a large language model (LLM), for automated scoring of Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) protocols. …”