{"id":"W2096990970","doi":"10.1107/s090744490603575x","title":"Macromolecular recognition in the Protein Data Bank","year":2006,"lang":"en","type":"article","venue":"Acta Crystallographica Section D Biological Crystallography","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":112,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Vrije Universiteit Brussel; University of Toronto","keywords":"Macromolecule; Protein Data Bank; Chemistry; Biophysics; Protein crystallization; Docking (animal); Crystallography; Molecular recognition; Protein structure; Structural biology; Macromolecular Substances; Biology; Biochemistry; Molecule; Crystallization","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002077318,0.003260795,0.00481767,0.002698456,0.001418155,0.004326263,0.003263482,0.002315425,0.1835106],"category_scores_gemma":[0.004807254,0.001279591,0.001284842,0.006592791,0.0005459529,0.002841225,0.001554269,0.004661933,0.2750114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001626037,"about_ca_system_score_gemma":0.003893563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004959821,"about_ca_topic_score_gemma":0.003926248,"domain_scores_codex":[0.9990402,0.0001705105,0.0001511554,0.0002331531,0.0002659555,0.0001390813],"domain_scores_gemma":[0.9982303,0.000240221,0.0001929217,0.0004903289,0.0006031664,0.0002430591],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0008640616,0.0001263872,0.0007859357,0.001927209,0.000176888,0.0001900364,0.00005507586,0.0007525735,0.005532278,0.009780448,0.9503161,0.02949296],"study_design_scores_gemma":[0.000584337,0.00007225329,0.002079813,0.0002339431,0.0001431457,0.0001861001,0.00003071128,0.002125134,0.002554774,0.00586319,0.9860703,0.00005621583],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.001761374,0.004808683,0.01429504,0.00197108,0.001538682,0.0004763388,0.8953907,0.01641703,0.06334125],"genre_scores_gemma":[0.003312147,0.002841062,0.01671168,0.0006886405,0.0001529156,0.0004564821,0.9633312,0.001043921,0.01146198],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1835106,"threshold_uncertainty_score":0.6139042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01812137208706128,"score_gpt":0.2333040890279291,"score_spread":0.2151827169408678,"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."}}