{"id":"W1987547168","doi":"10.1063/1.1522373","title":"Exploring the energy landscape of proteins: A characterization of the activation-relaxation technique","year":2002,"lang":"en","type":"article","venue":"The Journal of Chemical Physics","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Energy landscape; Maxima and minima; Energy (signal processing); Biomolecule; Relaxation (psychology); Range (aeronautics); Representation (politics); Statistical physics; Computer science; Biological system; Chemistry; Physics; Mathematics; Nanotechnology; Materials science; Statistics; Biology","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":[0.0001155987,0.00006204005,0.0000892963,0.000008129202,0.00002956418,0.00000355733,0.0002432118,0.00004153706,0.0000021945],"category_scores_gemma":[0.00005856253,0.00002966725,0.00007782925,0.0001116542,0.00006788278,0.00001238871,0.00005034775,0.0001077175,6.263917e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006366437,"about_ca_system_score_gemma":0.00001752544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002563859,"about_ca_topic_score_gemma":1.357786e-7,"domain_scores_codex":[0.9994923,0.00004920679,0.0002115517,0.00004119189,0.0001485032,0.00005719148],"domain_scores_gemma":[0.9991624,0.00001852107,0.0004778462,0.000193898,0.0001359715,0.00001132654],"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":[0.000039669,0.00002481681,0.00003209989,0.000009431421,0.00002432305,2.28233e-8,0.0001046402,0.00005839912,0.9963145,0.0002598088,0.00002288654,0.003109416],"study_design_scores_gemma":[0.0001142343,0.00004721811,0.0003125864,0.00003735871,0.00002015573,0.000006565455,0.00001319146,0.0001762391,0.9978047,0.001227785,0.0002054207,0.000034571],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.975997,0.00004224926,0.02349683,0.0002242132,0.00003617809,0.0001087274,0.000003025606,0.00000129183,0.00009045137],"genre_scores_gemma":[0.99942,0.000113173,0.0001233563,0.00005885654,0.0002499243,0.000008805265,0.000004716095,0.000007236176,0.00001391148],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02342299,"threshold_uncertainty_score":0.1209795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0158102799816076,"score_gpt":0.2030185805679157,"score_spread":0.1872083005863081,"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."}}