{"id":"W4392858819","doi":"10.21203/rs.3.rs-4088062/v1","title":"Rigorous Quality Assessment of Clinical Practice Guidelines for Microfluidic Technologies as Rapid Tests during COVID-19 using the AGREE II Instrument","year":2024,"lang":"en","type":"preprint","venue":"Research Square","topic":"Biosimilars and Bioanalytical Methods","field":"Immunology and Microbiology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"University of Toronto","keywords":"Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Clinical Practice; Quality (philosophy); Microfluidics; Medical physics; Computer science; Medicine; Virology; Nanotechnology; Materials science; Physics; Internal medicine; Family medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","research_integrity"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.02670339,0.0004419171,0.001190844,0.0004155078,0.0009888625,0.000110138,0.001390933,0.001876764,0.0002030852],"category_scores_gemma":[0.1005725,0.0002776828,0.0007369778,0.0005341425,0.001742099,0.000054877,0.007436585,0.004495186,0.00001413569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000485577,"about_ca_system_score_gemma":0.003830221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009329788,"about_ca_topic_score_gemma":0.00003450739,"domain_scores_codex":[0.9908192,0.004132895,0.002329687,0.001292147,0.0004781835,0.0009479531],"domain_scores_gemma":[0.9858227,0.008542905,0.0007115089,0.001695322,0.003104015,0.0001235854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.004755243,0.004338327,0.007252727,0.02709612,0.01012882,0.0002352509,0.001193903,0.00009545925,0.4291744,0.03214253,0.1689612,0.314626],"study_design_scores_gemma":[0.00394836,0.003417845,0.004277122,0.003592368,0.001145398,0.00033067,0.016807,0.0004095755,0.1220945,0.05969914,0.7829574,0.001320627],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4521054,0.221144,0.004052737,0.3034385,0.004915055,0.00962365,0.002364038,0.0007546992,0.001601866],"genre_scores_gemma":[0.8282028,0.04515728,0.1188233,0.002773049,0.0007741903,0.0009999984,0.0002698682,0.0001671969,0.002832255],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6139961,"threshold_uncertainty_score":0.9999675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5188351172130501,"score_gpt":0.6363066520693178,"score_spread":0.1174715348562677,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}