{"id":"W4365446494","doi":"10.1101/2023.04.11.536474","title":"PROTHON: A Local Order Parameter-Based Method for Efficient Comparison of Protein Ensembles","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Genome British Columbia; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Alberta Innovates; Compute Canada","keywords":"Python (programming language); Computer science; Molecular dynamics; Conformational ensembles; Representation (politics); Protein structure; Source code; Software; Algorithm; Biological system; Chemistry; Computational chemistry; Biology; Programming language","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":[0.003128696,0.0016391,0.002115566,0.003479609,0.00121913,0.002096784,0.003071305,0.001515391,0.01168429],"category_scores_gemma":[0.009118819,0.0009862821,0.001721021,0.001952773,0.0007917061,0.002347869,0.002619589,0.002508029,0.003860676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009531692,"about_ca_system_score_gemma":0.002203613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00296118,"about_ca_topic_score_gemma":0.004495825,"domain_scores_codex":[0.9984628,0.0004548849,0.00009330814,0.0003141558,0.0005787921,0.00009599484],"domain_scores_gemma":[0.9971645,0.001525083,0.0002564744,0.0004372108,0.0004141528,0.0002024542],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001565946,0.0005926848,0.006867814,0.001659269,0.001588553,0.0006628557,0.0005012601,0.3729772,0.03254164,0.04597419,0.09755322,0.4375153],"study_design_scores_gemma":[0.0000759194,0.00005696451,0.0006408367,0.00003023949,0.00003667639,0.00009739825,0.00003425485,0.973473,0.003344404,0.01574836,0.006417544,0.0000444429],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0169414,0.0004595397,0.9418111,0.0001787039,0.0002071068,0.0002009603,0.00265306,0.03600042,0.00154766],"genre_scores_gemma":[0.1396774,0.0002968715,0.837082,0.0002631794,0.0001648198,0.0009552371,0.007624371,0.01108007,0.002856043],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01168429,"threshold_uncertainty_score":0.03908789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01979824200811703,"score_gpt":0.2829255011581254,"score_spread":0.2631272591500084,"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."}}