{"id":"W5984741","doi":"","title":"A refined multisite fungal protein localizer","year":2008,"lang":"en","type":"article","venue":"International conference on Artificial intelligence and applications","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Subcellular localization; Classifier (UML); Protein subcellular localization prediction; Computer science; Artificial intelligence; Computational biology; Pattern recognition (psychology); Data mining; Biology; Cytoplasm; Biochemistry; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001838878,0.0009268947,0.001463315,0.001759057,0.0004845973,0.001016476,0.001998636,0.001556207,0.004307688],"category_scores_gemma":[0.002676194,0.0005105174,0.001297446,0.0008167949,0.0003044583,0.001492903,0.001014571,0.0009216615,0.003656226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006821979,"about_ca_system_score_gemma":0.0007585179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00226571,"about_ca_topic_score_gemma":0.002144437,"domain_scores_codex":[0.9988802,0.0001326965,0.00008108192,0.0004412748,0.0003680681,0.00009664558],"domain_scores_gemma":[0.9986113,0.000469581,0.0001637067,0.0002823968,0.0003868688,0.00008603657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002229429,0.0007258836,0.01708805,0.0008928023,0.0003123724,0.001211706,0.0002444429,0.05083016,0.3326634,0.003519462,0.01856804,0.5717143],"study_design_scores_gemma":[0.0001162293,0.0003965674,0.0078872,0.00003572151,0.00008689226,0.001113166,0.00003715041,0.8716559,0.1092857,0.001278628,0.008008639,0.00009807076],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1335282,0.000505035,0.7822303,0.0002619429,0.000148369,0.000321735,0.002941801,0.0783201,0.001742494],"genre_scores_gemma":[0.3686028,0.0001905894,0.6211389,0.0002885112,0.00005221208,0.0002739401,0.004440705,0.0007800405,0.004232157],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004307688,"threshold_uncertainty_score":0.01441067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06156228484602595,"score_gpt":0.3292272926304756,"score_spread":0.2676650077844497,"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."}}