{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001205293,0.0001416244,0.00009246906,0.0002182019,0.0009122578,0.0004214132,0.0006076096,0.00005049647,0.0001244229],"category_scores_gemma":[0.000108518,0.0001202111,0.00008514678,0.000594147,0.0008424431,0.00003661391,0.0002584626,0.0001367515,0.00007228427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003767177,"about_ca_system_score_gemma":0.0002392995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002481943,"about_ca_topic_score_gemma":0.000008658758,"domain_scores_codex":[0.9981059,0.0000228202,0.0002307894,0.0004323523,0.0006329882,0.0005750882],"domain_scores_gemma":[0.9990429,0.00000317837,0.00008623168,0.0002495672,0.0003169125,0.0003012252],"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":[0.00001751635,0.00001605976,0.0004776987,0.000002207625,0.000006599167,0.00000206865,0.00007603805,0.0001787731,0.9872223,0.0000741446,0.001574512,0.01035209],"study_design_scores_gemma":[0.0006993711,0.0006831869,0.003264272,0.00004132549,0.00001924385,0.0005660895,0.0001733127,0.003528722,0.9400947,0.001221144,0.04934777,0.0003608435],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8785163,0.0001918907,0.1079275,0.0007119916,0.003729289,0.0001017646,0.000001729909,0.00001827116,0.008801279],"genre_scores_gemma":[0.992396,0.00004017697,0.004182342,0.0001602558,0.001330259,0.000001040252,0.000001398834,0.00001303468,0.001875497],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1138797,"threshold_uncertainty_score":0.7016442,"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."}}