{"id":"W1521742603","doi":"10.1109/csb.2004.1332444","title":"Inverse protein folding in 2D HP model","year":2004,"lang":"en","type":"article","venue":"Proceedings. 2004 IEEE Computational Systems Bioinformatics Conference, 2004. CSB 2004.","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Fold (higher-order function); Inverse; Protein folding; Protein structure; Computer science; Protein structure prediction; Sequence (biology); Stability (learning theory); Protein design; Folding (DSP implementation); Computational biology; Algorithm; Mathematics; Chemistry; Biology; Engineering; Biochemistry; Machine learning; Geometry","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":[0.0003251871,0.0004360249,0.0006768223,0.0005084867,0.0004184152,0.0009851411,0.0008835794,0.001540214,0.003429141],"category_scores_gemma":[0.0009384629,0.0003241799,0.0007111131,0.0003825821,0.001118794,0.001236894,0.001027023,0.000776794,0.000718397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007129962,"about_ca_system_score_gemma":0.0004491791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002407522,"about_ca_topic_score_gemma":0.00106217,"domain_scores_codex":[0.9998047,0.00006767603,0.000006762432,0.00004182573,0.00005879958,0.00002025531],"domain_scores_gemma":[0.9997768,0.0000929856,0.00003262993,0.0000356466,0.00003200308,0.00002987383],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005046828,0.0000295672,0.0004349217,0.00007220043,0.00001764505,0.0002649034,0.00009696135,0.7758071,0.002696606,0.2135077,0.00192337,0.005098487],"study_design_scores_gemma":[0.000009905357,0.00001174515,0.00005779907,0.000003354659,0.000001984172,0.00004309968,0.000009142821,0.94857,0.0001694654,0.04989556,0.001221796,0.000006167245],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09427957,0.0008880019,0.8613143,0.001733104,0.0002032726,0.00007513662,0.0005769905,0.0004424907,0.04048722],"genre_scores_gemma":[0.8318999,0.001337214,0.1385687,0.0007198713,0.0001732121,0.0004041938,0.0006544465,0.0002300634,0.02601233],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003429141,"threshold_uncertainty_score":0.01147163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01500487766725089,"score_gpt":0.234366057293783,"score_spread":0.2193611796265321,"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."}}