{"id":"W4319872356","doi":"10.1016/j.bpj.2022.11.390","title":"Laws: Local alignment of water sites—Describing allosteric water networks in enzymes","year":2023,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Allosteric regulation; Protein dynamics; Biological system; Molecular dynamics; Function (biology); Computer science; Chemistry; Computational biology; Biology; Enzyme; Computational chemistry; Biochemistry; Genetics","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":[0.0008837479,0.0003938336,0.0005568386,0.0008907978,0.0006145161,0.001135368,0.001667414,0.001072851,0.002908365],"category_scores_gemma":[0.004397008,0.0004233771,0.0006978984,0.0008867402,0.001497324,0.003186131,0.000706809,0.0008578998,0.000345928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007029548,"about_ca_system_score_gemma":0.0006141046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003315412,"about_ca_topic_score_gemma":0.00296359,"domain_scores_codex":[0.9997571,0.00008907996,0.00001419997,0.00005761436,0.00005109888,0.0000308662],"domain_scores_gemma":[0.9987273,0.0007285193,0.0001660414,0.0001689532,0.00009922845,0.0001100011],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00006570601,0.00007287113,0.002082251,0.00006855684,0.00003160872,0.0001454804,0.0001290984,0.7522033,0.006883012,0.2249691,0.0016015,0.01174749],"study_design_scores_gemma":[0.000004434518,0.00000673303,0.0002273437,0.000002386478,0.000003210151,0.00001561683,0.00001307135,0.9505031,0.0004920302,0.0485006,0.0002258591,0.00000561012],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1576582,0.0001954643,0.8354899,0.0004837254,0.00005561985,0.0000615968,0.0002912577,0.000378725,0.005385674],"genre_scores_gemma":[0.9486563,0.0002147728,0.04742165,0.0001174003,0.0000617108,0.0001460525,0.0002081719,0.0002106093,0.0029634],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003315412,"threshold_uncertainty_score":0.009729505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01574301821905433,"score_gpt":0.2278665850031925,"score_spread":0.2121235667841381,"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."}}