{"id":"W2115024530","doi":"10.1142/s021972000400082x","title":"PAIRWISE PROTEIN STRUCTURE ALIGNMENT BASED ON AN ORIENTATION-INDEPENDENT BACKBONE REPRESENTATION","year":2004,"lang":"en","type":"article","venue":"Journal of Bioinformatics and Computational Biology","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Fudan University; Purdue University","keywords":"Pairwise comparison; Representation (politics); Structural alignment; Algorithm; Computer science; Orientation (vector space); Multiple sequence alignment; Dynamic programming; Protein structure; Artificial intelligence; Mathematics; Sequence alignment; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001655767,0.0001274816,0.0001504755,0.0001030359,0.00007805106,0.00003284016,0.0001088556,0.0001259874,0.000008337935],"category_scores_gemma":[0.00004240623,0.0001001474,0.00005870816,0.00006816148,0.00006691066,0.0000199941,0.00002847695,0.000106178,0.000001009029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002990936,"about_ca_system_score_gemma":0.0001635591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004483004,"about_ca_topic_score_gemma":0.000005199305,"domain_scores_codex":[0.9990776,0.00004514775,0.0004385445,0.0001227912,0.0001943521,0.000121527],"domain_scores_gemma":[0.9991759,0.00001481355,0.0003865553,0.0001199316,0.0002054693,0.00009734467],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001328654,0.0003649495,0.003846424,0.00009843498,0.0002440995,0.00001865636,0.000685429,0.8073387,0.1260715,0.02569526,0.0001918417,0.03411608],"study_design_scores_gemma":[0.0295079,0.03088186,0.0464741,0.0003656505,0.0002445365,0.001466154,0.002305058,0.2979598,0.1767529,0.4067875,0.005052255,0.002202346],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8110396,0.00004354105,0.1881591,0.0003109502,0.0001233285,0.0001834474,0.00004464745,0.000003755698,0.00009165038],"genre_scores_gemma":[0.9366941,0.00001034169,0.06224418,0.0005875441,0.0001249002,0.000003037799,0.0003229914,0.000006842889,0.000006025452],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5093789,"threshold_uncertainty_score":0.4083891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005996132849436699,"score_gpt":0.2523833834124025,"score_spread":0.2463872505629658,"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."}}