{"id":"W2084864412","doi":"10.1111/febs.12502","title":"Proteomics methods for subcellular proteome analysis","year":2013,"lang":"en","type":"review","venue":"FEBS Journal","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":104,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Canadian Institutes of Health Research","keywords":"Proteomics; Proteome; Protein subcellular localization prediction; Quantitative proteomics; Subcellular localization; Computational biology; Cell fractionation; Organelle; Complement (music); Biology; Cell biology; Bioinformatics; Biochemistry; Cytoplasm","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008107878,0.0005846438,0.002111782,0.0003760172,0.0003855217,0.0002724179,0.0009600476,0.0006700492,0.001112289],"category_scores_gemma":[0.0001482293,0.0004641373,0.002304413,0.0006526946,0.00006188441,0.0001372128,0.0001328045,0.001407213,0.00003901936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003370179,"about_ca_system_score_gemma":0.0002993004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003867092,"about_ca_topic_score_gemma":3.182624e-7,"domain_scores_codex":[0.9973897,0.00009759307,0.001255397,0.0005437554,0.0001825849,0.0005310032],"domain_scores_gemma":[0.9967263,0.0002032277,0.001691565,0.0008339541,0.0002785942,0.0002664025],"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":[0.000004237835,0.00004925725,5.993319e-7,0.005133339,0.001362251,0.000002634161,0.000009470623,0.000006238447,0.001073441,0.0003799725,0.0004199966,0.9915586],"study_design_scores_gemma":[0.000118394,0.00002050229,1.956632e-8,0.001259001,0.00463525,0.0001642379,0.000004662369,0.0002091648,0.003034964,0.007687946,0.9823418,0.0005241085],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[7.36678e-7,0.5033014,0.4948472,0.0000180012,0.0000247195,0.001319284,0.00007598439,0.00006633199,0.0003463036],"genre_scores_gemma":[5.154178e-8,0.509912,0.4834509,0.000005972307,0.0004068875,0.004038379,0.0001416242,0.00007741776,0.001966826],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9910344,"threshold_uncertainty_score":0.9998008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07663033483577882,"score_gpt":0.4430972071880006,"score_spread":0.3664668723522218,"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."}}