{"id":"W3159871407","doi":"10.15173/sciential.v1i1.1910","title":"Evading Evasion","year":2018,"lang":"en","type":"article","venue":"Sciential - McMaster Undergraduate Science Journal","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"CRISPR; Evasion (ethics); Computational biology; Genome editing; Computer science; Biology; Gene; Genetics; Immune system","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.00143792,0.001057032,0.0008368304,0.0008801646,0.0007439205,0.00230318,0.0008353398,0.001774187,0.009740625],"category_scores_gemma":[0.003127321,0.0002581791,0.0006660396,0.0003066673,0.00170285,0.001714586,0.003547088,0.002926686,0.003460712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007154209,"about_ca_system_score_gemma":0.0006353426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003604161,"about_ca_topic_score_gemma":0.000436557,"domain_scores_codex":[0.9979961,0.0003871891,0.00008659038,0.0003475023,0.000738141,0.0004445495],"domain_scores_gemma":[0.9984296,0.0004451644,0.0002219276,0.0003512113,0.0002949445,0.0002571115],"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":[0.0003320231,0.0002998404,0.005201146,0.001449774,0.0002501944,0.001824397,0.001296569,0.004471839,0.4541209,0.2484264,0.03468576,0.2476413],"study_design_scores_gemma":[0.0001029998,0.00119517,0.005249016,0.0007730805,0.0001323921,0.005394391,0.00161065,0.01100805,0.193102,0.1045059,0.6768097,0.0001166481],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2705703,0.05010089,0.2670576,0.01946011,0.006511865,0.000706105,0.001098957,0.003917939,0.3805762],"genre_scores_gemma":[0.8939754,0.01176746,0.01905044,0.009157668,0.0005241072,0.000266548,0.0005254084,0.0002419326,0.06449101],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009740625,"threshold_uncertainty_score":0.03258562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01188043831359732,"score_gpt":0.3204384375870833,"score_spread":0.308557999273486,"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."}}