{"id":"W2092368578","doi":"10.1142/s0218213005002351","title":"A COLLAPSING METHOD FOR THE EFFICIENT RECOVERY OF OPTIMAL EDGES IN PHYLOGENETIC TREES","year":2005,"lang":"en","type":"article","venue":"International Journal of Artificial Intelligence Tools","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Caprion (Canada)","funders":"","keywords":"Phylogenetic tree; Computer science; Context (archaeology); Inference; Set (abstract data type); Tree (set theory); Mathematical proof; Binary number; Algorithm; Enhanced Data Rates for GSM Evolution; Binary tree; Theoretical computer science; Combinatorics; Mathematics; Artificial intelligence; Biology; Paleontology","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":[0.002375645,0.0007088921,0.0009384473,0.001569768,0.001239439,0.001120432,0.001888837,0.001051586,0.003131117],"category_scores_gemma":[0.01117943,0.0007407403,0.001021484,0.001955978,0.001223355,0.001678366,0.002450479,0.002528081,0.001215711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004891008,"about_ca_system_score_gemma":0.001152416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001495344,"about_ca_topic_score_gemma":0.001828617,"domain_scores_codex":[0.9986801,0.0004128591,0.0001011732,0.0003133127,0.000393827,0.00009870956],"domain_scores_gemma":[0.9951751,0.002366208,0.0003589017,0.001359047,0.000539727,0.0002008871],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002724559,0.0001118227,0.002689512,0.0003059232,0.0001101302,0.0002953538,0.0006417689,0.1046614,0.03705386,0.07245714,0.005098783,0.7763018],"study_design_scores_gemma":[0.00005627502,0.0001123425,0.001256654,0.00003687344,0.0000405854,0.0003273535,0.00009713367,0.9057319,0.01503549,0.06786695,0.009378876,0.0000595292],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004286319,0.00006777182,0.995006,0.00003694482,0.00001395418,0.00002494682,0.00004236723,0.0003249946,0.0001967098],"genre_scores_gemma":[0.03293293,0.00008385965,0.9659795,0.00004986116,0.00002770112,0.00007043396,0.0002460338,0.0001596837,0.0004499662],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003131117,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04881618195269857,"score_gpt":0.3405609273709421,"score_spread":0.2917447454182435,"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."}}