{"id":"W2127061933","doi":"10.1177/1087057109335749","title":"Buffer Optimization of Thermal Melt Assays of Plasmodium Proteins for Detection of Small-Molecule Ligands","year":2009,"lang":"en","type":"article","venue":"SLAS DISCOVERY","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"Structural Genomics Consortium; University of Toronto","funders":"National Institute of Allergy and Infectious Diseases; National Institute of General Medical Sciences; Harvard University; Medicines for Malaria Venture; University of Washington; National Institutes of Health; University of Glasgow","keywords":"Recombinant DNA; Plasmodium falciparum; Plasmodium (life cycle); Buffer (optical fiber); Thermal stability; Chemistry; Small molecule; High-throughput screening; Chromatography; Biochemistry; Biology; Malaria; Computer science; Immunology; Organic chemistry","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":[0.00008154746,0.0001037172,0.0001649129,0.00003886556,0.00002085243,0.000006195749,0.0001051534,0.0001463886,0.000001544911],"category_scores_gemma":[0.00005647949,0.0000925893,0.0001188395,0.00006477543,0.00004799342,0.000009099139,0.0000273634,0.00003654998,6.177915e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006542392,"about_ca_system_score_gemma":0.00005823452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001479555,"about_ca_topic_score_gemma":0.00001538547,"domain_scores_codex":[0.9993889,0.00001528135,0.0002326695,0.0001611108,0.00008803316,0.0001139876],"domain_scores_gemma":[0.9994565,0.00000736651,0.0001955765,0.000209856,0.0001114719,0.00001919878],"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":[0.0003744502,0.00006279974,0.0001135487,0.00006101463,0.00003853842,1.397356e-7,0.00002250775,0.009707182,0.9885012,0.0003619683,0.000006023607,0.0007506564],"study_design_scores_gemma":[0.0005171464,0.0009791569,0.0009029023,0.00002245494,0.00003138649,0.000001399614,0.0000122579,0.003129225,0.993984,0.0003121744,0.00001489184,0.00009304116],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.689553,0.0001259705,0.3096392,0.00001468404,0.00004485368,0.000288052,0.00005005357,0.00000313748,0.0002810836],"genre_scores_gemma":[0.9955918,0.00002576277,0.004092583,0.00002495479,0.00005623343,0.00001780688,0.00009207111,0.00001160994,0.00008720319],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3060388,"threshold_uncertainty_score":0.3775682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005608488669415896,"score_gpt":0.2162849790701959,"score_spread":0.21067649040078,"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."}}