{"id":"W2127056957","doi":"10.1002/prot.20060","title":"The structural genomics experimental pipeline: Insights from global target lists","year":2004,"lang":"en","type":"article","venue":"Proteins Structure Function and Bioinformatics","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Biotechnology Research Institute; McGill University","funders":"Canadian Institutes of Health Research; National Institutes of Health","keywords":"Structural genomics; Pipeline (software); Protein Data Bank (RCSB PDB); Bottleneck; Genomics; Computational biology; Computer science; Data mining; Genome; Biology; Protein structure; Genetics; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006226764,0.001007139,0.001039221,0.002791707,0.0007469734,0.002071255,0.001284347,0.0005320256,0.003805127],"category_scores_gemma":[0.01329765,0.0005251089,0.0007510519,0.00513453,0.0005791939,0.003573939,0.00193324,0.001220852,0.002111818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00104813,"about_ca_system_score_gemma":0.002347585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003437408,"about_ca_topic_score_gemma":0.003775173,"domain_scores_codex":[0.9980485,0.0005667972,0.0001307405,0.0002946659,0.0008115531,0.0001476809],"domain_scores_gemma":[0.9917265,0.003571694,0.0007200146,0.002176425,0.001470562,0.0003348598],"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":[0.00242369,0.0005666626,0.1224167,0.001902146,0.000477901,0.0007368827,0.001824312,0.07893394,0.09375139,0.05392078,0.08020977,0.5628358],"study_design_scores_gemma":[0.0002810642,0.0007605626,0.1068064,0.000225869,0.0003438984,0.0008750537,0.001248178,0.6075428,0.0728844,0.1109058,0.09789958,0.000226447],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2076528,0.001121079,0.6863075,0.004174416,0.00006797336,0.0003866155,0.04250618,0.04432265,0.01346082],"genre_scores_gemma":[0.571633,0.001432971,0.3080541,0.0007374513,0.00008764599,0.0007488879,0.1077155,0.006955945,0.002634506],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006226764,"threshold_uncertainty_score":0.03293067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004859359575702844,"score_gpt":0.2090562975216376,"score_spread":0.2041969379459348,"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."}}