{"id":"W2069982947","doi":"10.1002/prot.1163","title":"Probabilistic sampling of protein conformations: New hope for brute force?","year":2001,"lang":"en","type":"article","venue":"Proteins Structure Function and Bioinformatics","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":121,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; University of Toronto; Mount Sinai Hospital","funders":"","keywords":"Conformational isomerism; Probabilistic logic; Protein structure; Sampling (signal processing); Algorithm; Protein structure prediction; Computer science; Protein secondary structure; Sequence (biology); Statistical physics; Mathematics; Artificial intelligence; Physics; Chemistry; Molecule","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":[0.01356296,0.001229822,0.00259367,0.001213616,0.001568459,0.00249426,0.002772828,0.003290999,0.003280544],"category_scores_gemma":[0.04401537,0.001121517,0.001778389,0.0009568457,0.006238346,0.008563434,0.003183988,0.006774604,0.0009553801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001452661,"about_ca_system_score_gemma":0.001502546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004221076,"about_ca_topic_score_gemma":0.002810895,"domain_scores_codex":[0.9947959,0.002735761,0.0001533591,0.0008249706,0.001220615,0.000269509],"domain_scores_gemma":[0.9726059,0.02129672,0.0006395581,0.003965031,0.0009457953,0.0005470425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006305589,0.0003537262,0.006166338,0.000386939,0.0003556098,0.0001912507,0.0006774564,0.3616168,0.003809637,0.499925,0.008807188,0.1170796],"study_design_scores_gemma":[0.0001296293,0.0001468192,0.0003969508,0.00006213188,0.00002864352,0.00006927717,0.00008402563,0.5669066,0.0009868715,0.4238239,0.007288845,0.00007639349],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03087254,0.003844301,0.9477351,0.01166527,0.0004068718,0.00007371105,0.00009572856,0.0009867876,0.004319753],"genre_scores_gemma":[0.4407667,0.005045447,0.5422177,0.003767336,0.001305953,0.0005344427,0.0003644687,0.0007410477,0.005256747],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01356296,"threshold_uncertainty_score":0.07172865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01168964491533693,"score_gpt":0.2359132571651796,"score_spread":0.2242236122498427,"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."}}