{"id":"W4281961566","doi":"10.3390/ijtm2020017","title":"CRISPR-Based Diagnostics for Point-of-Care Viral Detection","year":2022,"lang":"en","type":"article","venue":"International Journal of Translational Medicine","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"CRISPR; Point-of-care testing; Point of care; Molecular diagnostics; Computational biology; Computer science; Multiplex; Risk analysis (engineering); Standardization; Nanotechnology; Biochemical engineering; Data science; Biology; Bioinformatics; Medicine; Engineering; Genetics; Immunology; Materials science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001689838,0.0008120527,0.001147938,0.00104996,0.0004215255,0.001965804,0.0009410532,0.001671081,0.003041867],"category_scores_gemma":[0.001753781,0.0004489398,0.0009468745,0.0005486176,0.001000003,0.0008694619,0.001190373,0.002283724,0.001698449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009010598,"about_ca_system_score_gemma":0.0008574529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005496609,"about_ca_topic_score_gemma":0.0009155697,"domain_scores_codex":[0.9981955,0.0004455697,0.0001414447,0.0003534875,0.0007024082,0.000161569],"domain_scores_gemma":[0.9991512,0.0003932437,0.000137236,0.0000909321,0.0001476089,0.00007981485],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002709813,0.0001377142,0.001934606,0.00474809,0.0001812177,0.0008005696,0.0002879885,0.003746405,0.7206694,0.03091479,0.01330473,0.2230036],"study_design_scores_gemma":[0.00007499767,0.001171521,0.002964653,0.0009857491,0.0002501303,0.003765257,0.0002235509,0.01090335,0.544886,0.01351125,0.421059,0.0002045342],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08281277,0.2332059,0.6090905,0.009808958,0.004084122,0.001102235,0.003286802,0.008194148,0.04841455],"genre_scores_gemma":[0.4249057,0.1751605,0.371299,0.004460832,0.0008704602,0.0008789425,0.003208081,0.0004852859,0.01873119],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003041867,"threshold_uncertainty_score":0.01017606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008042945079267658,"score_gpt":0.3257786854037178,"score_spread":0.3177357403244502,"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."}}