{"id":"W1989890061","doi":"10.1586/14789450.5.4.603","title":"Complementary methods to assist subcellular fractionation in organellar proteomics","year":2008,"lang":"en","type":"review","venue":"Expert Review of Proteomics","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Clinical Research Institute","funders":"","keywords":"Proteomics; Proteome; Cell fractionation; Organelle; Computational biology; Differential centrifugation; Subcellular localization; Biology; Quantitative proteomics; Identification (biology); Computer science; Bioinformatics; Cell biology; Biochemistry; Enzyme; Cytoplasm","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007477462,0.0008229286,0.003017655,0.0002920932,0.0001415856,0.00002287588,0.001074178,0.0005139564,0.0006368096],"category_scores_gemma":[0.0003573193,0.0007836969,0.0007445982,0.0009207448,0.00009760831,0.000134657,0.0003781887,0.0009770562,0.00005265603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009549822,"about_ca_system_score_gemma":0.0004911941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008037936,"about_ca_topic_score_gemma":0.000005367223,"domain_scores_codex":[0.9953324,0.0002525468,0.002543033,0.0009791839,0.0004211564,0.0004716683],"domain_scores_gemma":[0.9963105,0.0002107713,0.001611958,0.001446627,0.0002341317,0.0001859888],"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":[0.00001882498,0.0004002326,0.00000458303,0.1441277,0.000148829,0.00001611977,0.00009954061,0.000003586543,0.01091539,0.001060795,0.003974026,0.8392304],"study_design_scores_gemma":[0.0001397611,0.00003041779,1.068765e-7,0.06829964,0.00009327546,0.00007760163,0.00001057027,0.00001326242,0.0206808,0.0003544471,0.9096198,0.000680329],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000001218087,0.7541816,0.2396988,0.0001914606,0.00005880033,0.005022486,0.0001571266,0.00009204335,0.0005965275],"genre_scores_gemma":[4.863092e-8,0.5122074,0.4824748,0.0001889886,0.0001473039,0.004169653,0.0006285441,0.00009887348,0.00008440209],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9056458,"threshold_uncertainty_score":0.9994614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05765447516257207,"score_gpt":0.4468254692699157,"score_spread":0.3891709941073437,"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."}}