{"id":"W2114456327","doi":"10.1080/10635150701286549","title":"Seeing the Trees for the Network: Consensus, Information Content, and Superphylogenies","year":2007,"lang":"en","type":"article","venue":"Systematic Biology","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Biology; Content (measure theory); Mathematics","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":[0.001143224,0.0001148918,0.0001883309,0.00001121037,0.0002879351,0.00002568424,0.0001438546,0.00009510268,6.336192e-7],"category_scores_gemma":[0.0001987352,0.0000564041,0.00006599702,0.0000318119,0.0002102071,5.458302e-7,0.000116985,0.00004080289,0.000001297237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004252322,"about_ca_system_score_gemma":0.00001641882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000252671,"about_ca_topic_score_gemma":0.0001734341,"domain_scores_codex":[0.99919,0.00007921915,0.0003429184,0.0001163056,0.00003324472,0.0002382765],"domain_scores_gemma":[0.9990869,0.0004219838,0.0001404772,0.0002298687,0.00009766562,0.0000231108],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0005994217,0.00004731013,0.2147174,0.007192937,0.003358209,0.000001328372,0.005125015,0.0008167418,0.6812522,0.07616674,0.003138011,0.007584712],"study_design_scores_gemma":[0.009498744,0.004296693,0.6701525,0.001747381,0.002234757,0.001025799,0.07815377,0.008338852,0.07133734,0.02044966,0.1296953,0.003069257],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9684237,0.01520315,0.01390634,0.0006803243,0.0003232253,0.001295143,0.00002276365,0.000004220015,0.0001411331],"genre_scores_gemma":[0.9984844,0.0001393033,0.0005062965,0.0005221032,0.0001904806,0.00010866,0.00001169423,0.000005664628,0.00003141516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6099148,"threshold_uncertainty_score":0.2300092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02571795915562187,"score_gpt":0.2464800234698619,"score_spread":0.22076206431424,"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."}}