{"id":"W6968561963","doi":"10.5281/zenodo.3669099","title":"Generation of Knockout Cell Lines Using CRISPR-Cas9 Technology","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Cell culture; Cell; Genome; Set (abstract data type); Protocol (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":[0.001462496,0.0009869457,0.001409449,0.001581378,0.001290219,0.001189026,0.002155215,0.001239768,0.01518558],"category_scores_gemma":[0.0007306638,0.001048759,0.001036328,0.001041151,0.0005767442,0.0006316855,0.001153113,0.00343921,0.01505352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005153369,"about_ca_system_score_gemma":0.001172746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001468308,"about_ca_topic_score_gemma":0.00325238,"domain_scores_codex":[0.9986726,0.0001451132,0.0001806249,0.0002661499,0.0005651274,0.0001703725],"domain_scores_gemma":[0.9993827,0.000114592,0.00007108622,0.0001775486,0.0001313731,0.0001225493],"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":[0.0001662222,0.0001342842,0.0003346278,0.0002613663,0.00003692003,0.0003392993,0.00011794,0.0002993475,0.9794287,0.002745637,0.007347406,0.008788274],"study_design_scores_gemma":[0.0001509928,0.000257901,0.002335787,0.0001059087,0.0001164227,0.001468225,0.00009676433,0.002153636,0.7665334,0.001039435,0.2256438,0.0000977388],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1613763,0.004992737,0.6701439,0.001370812,0.002429729,0.01008596,0.08477481,0.01667717,0.04814858],"genre_scores_gemma":[0.2658175,0.00794728,0.4229634,0.001433787,0.0001962264,0.01416072,0.1380737,0.005885439,0.143522],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01518558,"threshold_uncertainty_score":0.05080086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05297389630115775,"score_gpt":0.2940586908392702,"score_spread":0.2410847945381124,"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."}}