{"id":"W4300817977","doi":"10.1155/2022/1839946","title":"Molecular Characterization and In Silico Analyses of Maurolipin Structure as a Secretory Phospholipase <a:math xmlns:a=\"http://www.w3.org/1998/Math/MathML\" id=\"M1\"> <a:msub> <a:mrow> <a:mi>A</a:mi> </a:mrow> <a:mrow> <a:mn>2</a:mn> </a:mrow> </a:msub> </a:math> (<c:math xmlns:c=\"http://www.w3.org/1998/Math/MathML\" id=\"M2\"> <c:msub> <c:mrow> <c:mtext>sPLA</c:mtext> </c:mrow> <c:mrow> <c:mn>2</c:mn> </c:mrow> </c:msub> </c:math>) from Venom Glands of Iranian Scorpio maurus (Arachnida: Scorpionida)","year":2022,"lang":"lv","type":"article","venue":"Journal of Tropical Medicine","topic":"Venomous Animal Envenomation and Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Shiraz University; Shiraz University of Medical Sciences","keywords":"In silico; Computational biology; Characterization (materials science); Computer science; Biology; Physics; 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":[0.0003804646,0.001007818,0.0007292486,0.0006432094,0.0004682613,0.001134747,0.0006048056,0.0007457386,0.004767005],"category_scores_gemma":[0.0005785578,0.0002655367,0.002032159,0.0005034435,0.000133708,0.0004092262,0.0002274249,0.000599519,0.002108035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006245602,"about_ca_system_score_gemma":0.0006284593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004183237,"about_ca_topic_score_gemma":0.006298966,"domain_scores_codex":[0.9998575,0.00002562797,0.00001032084,0.0000506804,0.00003602969,0.00001978956],"domain_scores_gemma":[0.9998606,0.00006260829,0.00002481249,0.0000118014,0.00002159461,0.0000186057],"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":[0.004622756,0.00147517,0.05723342,0.002019475,0.001394865,0.004487503,0.0004043659,0.1238343,0.7118389,0.00527809,0.01589807,0.07151312],"study_design_scores_gemma":[0.0004130662,0.001015627,0.03958551,0.000128264,0.001094786,0.001186447,0.0002886329,0.7211697,0.2031119,0.001962988,0.02994679,0.0000962726],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9321575,0.003141739,0.03414882,0.0009056863,0.0001373418,0.0002295966,0.01803345,0.003762654,0.007483276],"genre_scores_gemma":[0.8486528,0.002682232,0.05754584,0.0003551352,0.00004579164,0.0002189797,0.08343983,0.0004507971,0.006608557],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004767005,"threshold_uncertainty_score":0.01594722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01615692411004692,"score_gpt":0.2561118086977711,"score_spread":0.2399548845877242,"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."}}