{"id":"W2026060326","doi":"10.1109/tkde.2012.151","title":"NHOP: A Nested Associative Pattern for Analysis of Consensus Sequence Ensembles","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Knowledge and Data Engineering","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Associative property; Computer science; Sequence (biology); Tree (set theory); Theoretical computer science; Tree structure; Pattern recognition (psychology); Core (optical fiber); Artificial intelligence; Algorithm; Data mining; Computational biology; Mathematics; Combinatorics; Biology; Binary tree","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001984375,0.0008609257,0.0009477355,0.002421958,0.0006090222,0.001184143,0.001482195,0.0009555029,0.005141777],"category_scores_gemma":[0.007433356,0.0004137431,0.0008227124,0.002444376,0.0007963026,0.00247903,0.001711871,0.001120064,0.001835782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003586024,"about_ca_system_score_gemma":0.0009719817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00150659,"about_ca_topic_score_gemma":0.001675549,"domain_scores_codex":[0.9987197,0.0003358168,0.000135118,0.0003216713,0.0003984346,0.00008919636],"domain_scores_gemma":[0.9974204,0.001404015,0.0001961808,0.0005155685,0.0003323945,0.0001313352],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000765333,0.0003305871,0.01435136,0.000620213,0.0002996457,0.0005911019,0.0004471481,0.09487472,0.02817808,0.04636979,0.009769653,0.8034023],"study_design_scores_gemma":[0.00005405517,0.0001500123,0.002054927,0.00003208875,0.00003427499,0.0003268991,0.0001018056,0.9210191,0.007806563,0.06183031,0.006551661,0.00003832252],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009858163,0.00006526373,0.9859053,0.00005320426,0.00002585403,0.00008524181,0.000633841,0.002844972,0.0005280752],"genre_scores_gemma":[0.1339486,0.0001142752,0.8612959,0.00009914569,0.00004864409,0.0004966938,0.002173655,0.0005890465,0.001234096],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005141777,"threshold_uncertainty_score":0.01720095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03855882831999959,"score_gpt":0.2947681018071184,"score_spread":0.2562092734871188,"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."}}