{"id":"W1979330256","doi":"10.1007/s00299-010-0925-6","title":"Tail-anchored membrane proteins: exploring the complex diversity of tail-anchored-protein targeting in plant cells","year":2010,"lang":"en","type":"review","venue":"Plant Cell Reports","topic":"Phytase and its Applications","field":"Agricultural and Biological Sciences","cited_by":35,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Biotechnology and Biological Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; University of Guelph","keywords":"Biology; FERM domain; Biogenesis; Cell biology; Membrane protein; Protein targeting; Organelle; Integral membrane protein; Context (archaeology); Cytosol; Protein domain; Organelle biogenesis; Membrane; Transport protein; Biochemistry; Protein subcellular localization prediction; Protein Sorting Signals; Peptide sequence; Gene; Signal peptide","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005501584,0.000808352,0.001307598,0.001584138,0.0001854571,0.0009604416,0.0009016804,0.0009450629,0.001291854],"category_scores_gemma":[0.0003673811,0.0002883369,0.0002972446,0.002494317,0.000497232,0.001437289,0.0005780761,0.001151417,0.001916203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000638288,"about_ca_system_score_gemma":0.0006816331,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007787878,"about_ca_topic_score_gemma":0.001415792,"domain_scores_codex":[0.9998826,0.0000109604,0.00001467559,0.0000255189,0.00005295184,0.00001332982],"domain_scores_gemma":[0.9998373,0.000067213,0.00002621172,0.000006517351,0.00004450391,0.00001824026],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008292135,0.00005550139,0.0001573017,0.00943431,0.00007249136,0.0003069415,0.00005684786,0.000434466,0.0281188,0.004094413,0.01053454,0.9466513],"study_design_scores_gemma":[0.00002428224,0.0001284426,0.001189174,0.001341036,0.0001138634,0.002138924,0.0001059909,0.0002055908,0.01009667,0.002852877,0.9817693,0.00003382087],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003782845,0.9982055,0.0004656541,0.0001240897,0.00009344419,0.000003606013,0.00001734895,0.000008511546,0.0007035684],"genre_scores_gemma":[0.001219117,0.9974347,0.0005084663,0.00007168113,0.00005997379,0.000003710112,0.00003140309,0.00000143322,0.0006696238],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.001584138,"threshold_uncertainty_score":0.004631162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08218027749376822,"score_gpt":0.2398229988672967,"score_spread":0.1576427213735285,"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."}}