{"id":"W2898847664","doi":"10.21203/rs.3.rs-878139/v1","title":"PSL-Recommender: Protein Subcellular Localization Prediction using Recommender System","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network","funders":"Iran National Science Foundation; National Science Foundation","keywords":"Recommender system; Computer science; PSL; Machine learning; Inference; Artificial intelligence; Matrix decomposition; Data mining; Mathematics","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":[0.002186383,0.0003650918,0.0003514332,0.0002765953,0.0004138597,0.0003433168,0.0004924974,0.0009631219,0.00008867842],"category_scores_gemma":[0.0005187705,0.0003850939,0.0002089856,0.0003132501,0.00009897871,0.00001142871,0.001798505,0.001521272,0.00001940469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004497007,"about_ca_system_score_gemma":0.0006071094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002487809,"about_ca_topic_score_gemma":0.00003278557,"domain_scores_codex":[0.9956921,0.001326053,0.0006435183,0.0007618597,0.0009166317,0.0006598674],"domain_scores_gemma":[0.9973276,0.00003259625,0.0002709109,0.001228589,0.0009444779,0.0001958588],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001084204,0.001925566,0.06434187,0.09368469,0.002925959,0.0002986714,0.005271494,0.4557743,0.2863666,0.00177594,0.06327525,0.02327541],"study_design_scores_gemma":[0.001054942,0.0005995813,0.0003726104,0.004917402,0.00007367608,0.00009872721,0.00466751,0.8842424,0.05599681,0.00008689723,0.04688606,0.001003453],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4535563,0.004162101,0.5293259,0.0005910631,0.001292596,0.004545335,0.0003265743,0.0002728461,0.005927302],"genre_scores_gemma":[0.9851121,0.0003112543,0.006577794,0.00005233542,0.0007574843,0.0002418444,0.006310926,0.0001136183,0.0005226473],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5315558,"threshold_uncertainty_score":0.9998601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0551759197009809,"score_gpt":0.3660431512395883,"score_spread":0.3108672315386074,"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."}}