{"id":"W2591652900","doi":"10.1038/protex.2017.026","title":"Generation of FLIP and FLIP-FlpE targeting vectors for conditional and reversible gene knockouts","year":2017,"lang":"en","type":"article","venue":"Protocol Exchange","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"L'Alliance Boviteq","funders":"","keywords":"Flip; Gene knockout; Computational biology; Conditional gene knockout; Gene; Genetics; Biology; Computer science; Cell biology; Phenotype","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":[0.000872933,0.0008334407,0.0007979129,0.0009214643,0.000583417,0.0005416065,0.001040195,0.0008214755,0.008056167],"category_scores_gemma":[0.000683333,0.0005563163,0.0004522648,0.0006377092,0.0004443219,0.0006074984,0.0008125649,0.001745642,0.004871049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003930537,"about_ca_system_score_gemma":0.0007585555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003990181,"about_ca_topic_score_gemma":0.0008035318,"domain_scores_codex":[0.999337,0.0000785787,0.00006807214,0.0001112436,0.0002929728,0.0001121955],"domain_scores_gemma":[0.9996876,0.00005161894,0.00005009697,0.0000713008,0.00006883586,0.00007059928],"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":[0.0001079926,0.00006281758,0.00009230284,0.0002473952,0.00001495631,0.0002092939,0.00005517976,0.0003156849,0.9782859,0.003508767,0.00269288,0.01440682],"study_design_scores_gemma":[0.00005279302,0.0001511224,0.0005378929,0.00004460205,0.00002949413,0.000699928,0.00002772554,0.001175812,0.9231007,0.000624724,0.0735227,0.00003252031],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"protocol","genre_scores_codex":[0.2543413,0.004961993,0.6766458,0.0009403385,0.001200541,0.005695092,0.02040698,0.006482756,0.02932524],"genre_scores_gemma":[0.4095403,0.009008973,0.4427304,0.0007052355,0.0001420449,0.008209105,0.03984299,0.002336663,0.08748429],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.008056167,"threshold_uncertainty_score":0.02695054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04099159183153085,"score_gpt":0.3625465830521922,"score_spread":0.3215549912206613,"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."}}