{"id":"W2111515098","doi":"10.1371/journal.pone.0074483","title":"Proteomic Amino-Termini Profiling Reveals Targeting Information for Protein Import into Complex Plastids","year":2013,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Wenner-Gren Foundation; Deutscher Akademischer Austauschdienst; Centre for Blood Research, University of British Columbia; Bundesministerium für Bildung und Forschung; Michael Smith Health Research BC; Breast Cancer Society of Canada; University of British Columbia; Alexander von Humboldt-Stiftung","keywords":"Plastid; Biology; Eukaryote; Transit Peptide; Endosymbiosis; Biochemistry; Thalassiosira pseudonana; Chloroplast; Cell biology; Sequence motif; Genome; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001520292,0.0001493376,0.000185182,0.00003394804,0.0001404217,0.00004343581,0.0001352574,0.0000915452,0.0000122411],"category_scores_gemma":[0.0001771522,0.000142562,0.00005301087,0.00003601444,0.0000336415,0.00000501667,0.0001174088,0.00005243011,0.00002616146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001513016,"about_ca_system_score_gemma":0.00004168932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002249587,"about_ca_topic_score_gemma":0.000001631631,"domain_scores_codex":[0.999083,0.0000183564,0.0003405783,0.0001990185,0.0001096721,0.000249402],"domain_scores_gemma":[0.9993742,0.000006630029,0.0001634909,0.0001852257,0.0002126521,0.00005787595],"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":[0.00002916093,0.00008510193,0.006011455,0.0002306691,0.0001059867,7.333279e-8,0.00009308237,0.000005337193,0.9926038,0.00003651967,0.0003866465,0.0004121664],"study_design_scores_gemma":[0.000488714,0.0004116017,0.008071566,0.000047025,0.00002986115,7.964917e-7,0.00008560331,0.000768901,0.9886796,0.0004595755,0.0007198224,0.0002369693],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963239,0.00007354118,0.0005642024,0.0001513108,0.00002496634,0.002566263,0.00003053586,0.00000943814,0.000255821],"genre_scores_gemma":[0.9315001,0.00001702813,0.06619972,0.0001207002,0.0002161451,0.001495527,0.0002681998,0.0000177018,0.0001648255],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06563552,"threshold_uncertainty_score":0.5813508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0265620024073515,"score_gpt":0.227647759666158,"score_spread":0.2010857572588065,"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."}}