{"id":"W2059579166","doi":"10.1016/j.bbrc.2009.09.036","title":"Meta prediction of protein crystallization propensity","year":2009,"lang":"en","type":"article","venue":"Biochemical and Biophysical Research Communications","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Structural genomics; Crystallization; Computer science; Complementarity (molecular biology); Selection (genetic algorithm); Protein crystallization; Isoelectric point; Genomics; Algorithm; Data mining; Mathematics; Protein structure; Artificial intelligence; Biology; Genome; Chemistry; Genetics","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":[],"consensus_categories":[],"category_scores_codex":[0.0002729759,0.00008690407,0.0001431426,0.00003858506,0.0001421763,0.000019013,0.0003673909,0.0001191042,0.000003305833],"category_scores_gemma":[0.0001968372,0.00006718922,0.0000712578,0.0002151674,0.0004463104,0.000006568245,0.0002545805,0.0001846656,0.000001155611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008856059,"about_ca_system_score_gemma":0.00005097978,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001622441,"about_ca_topic_score_gemma":0.000002502743,"domain_scores_codex":[0.9990887,0.0001401936,0.0001690645,0.0002144289,0.0002249218,0.0001627115],"domain_scores_gemma":[0.9988022,0.00002299548,0.00004334603,0.0007375681,0.0003063769,0.00008752806],"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":[0.00004687698,0.0001560575,0.00002518797,0.00001376075,0.0000614759,9.430381e-8,0.00001060715,3.375611e-7,0.9920965,0.005940121,0.0001494079,0.00149951],"study_design_scores_gemma":[0.0002010826,0.0004113095,0.002525316,0.00001690762,0.0000633517,0.000002368501,0.00001196405,0.0003782366,0.9856904,0.007383022,0.003222645,0.00009338106],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9932985,0.001820244,0.001530356,0.00169789,0.000006164366,0.0005588776,0.00006969149,0.00001646992,0.00100183],"genre_scores_gemma":[0.9960365,0.0004209683,0.003065633,0.00003372428,0.00005424077,0.00003949556,0.0002246197,0.000005249813,0.0001195105],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006406148,"threshold_uncertainty_score":0.2739897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09085157125937662,"score_gpt":0.3398759375403985,"score_spread":0.2490243662810219,"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."}}