{"id":"W2900724112","doi":"10.1101/474379","title":"Identification of a putative nuclear localization signal in maspin protein shed light into its nuclear import regulation","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Silk-based biomaterials and applications","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Universidade de São Paulo; Fundação de Amparo à Pesquisa do Estado de São Paulo; Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Maspin; Nuclear localization sequence; Subcellular localization; Nuclear export signal; Cell biology; Cell nucleus; Nuclear transport; Biology; Nuclear protein; Nucleus; NLS; HeLa; Gene; Cell; Biochemistry; Genetics; Cytoplasm; Transcription factor; Cancer","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"],"consensus_categories":[],"category_scores_codex":[0.001253583,0.0004143351,0.0005460555,0.0003613531,0.0001943707,0.0002838945,0.0005871797,0.0005146168,0.0003405716],"category_scores_gemma":[0.0001578546,0.0004470689,0.00009270387,0.0006902401,0.0002020257,0.0003395861,0.0003332181,0.0001773224,0.0002889982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000346362,"about_ca_system_score_gemma":0.0003167558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001056604,"about_ca_topic_score_gemma":0.000003330678,"domain_scores_codex":[0.9965512,0.0002572677,0.001287363,0.001042777,0.0005013131,0.0003600934],"domain_scores_gemma":[0.996788,0.00001870312,0.001365087,0.0009111742,0.0007834203,0.0001336135],"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":[0.00007999673,0.0001903916,0.0001488737,0.0004302024,0.00001748696,0.000002846473,0.0001022512,0.0002545396,0.9968081,0.00189503,0.00006885752,0.00000149627],"study_design_scores_gemma":[0.0003189891,0.00006479272,0.01556695,0.0003835405,0.00004183023,1.198468e-8,0.00000946275,0.006856212,0.9759784,0.00005947909,0.0002758609,0.0004444583],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937353,0.00006936213,0.003316777,0.0002558584,0.0003669639,0.001773637,0.000215268,0.0002621597,0.00000470268],"genre_scores_gemma":[0.9963222,0.00001334028,0.002918187,0.00004604643,0.000250428,0.0003255336,0.000003688984,0.000117568,0.000002992365],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02082961,"threshold_uncertainty_score":0.9997981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01044267151473857,"score_gpt":0.2272575602509546,"score_spread":0.216814888736216,"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."}}