{"id":"W6929696251","doi":"10.5061/dryad.ffbg79ctw","title":"Supplementary material for: Building alternative consensus trees and supertrees using k-means and Robinson and Foulds distance","year":2021,"lang":"en","type":"dataset","venue":"Open MIND","topic":"HIV, Drug Use, Sexual Risk","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Supertree; Phylogenetic tree; Tree rearrangement; Tree (set theory); Cluster analysis; Partition (number theory); Inference; Set (abstract data type); Computational phylogenetics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001751044,0.00226294,0.001734273,0.003155177,0.001442518,0.002728323,0.004361221,0.002005742,0.5658749],"category_scores_gemma":[0.02049531,0.001628726,0.001686417,0.004475821,0.000531687,0.003012111,0.00225352,0.002224958,0.2139859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001298758,"about_ca_system_score_gemma":0.002343058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006400118,"about_ca_topic_score_gemma":0.01516571,"domain_scores_codex":[0.9987751,0.000254548,0.0001342498,0.000357572,0.0003913413,0.00008713463],"domain_scores_gemma":[0.993131,0.004097548,0.000245508,0.0008036044,0.001458829,0.0002635105],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002284548,0.00009499657,0.0007627488,0.001457331,0.00008391889,0.0002652855,0.0001384359,0.01084634,0.002075611,0.01198446,0.8665679,0.1054944],"study_design_scores_gemma":[0.0007518061,0.0001144774,0.002843501,0.0006949066,0.00009308286,0.0005875696,0.0002235597,0.1236161,0.005703067,0.1113637,0.7537723,0.0002359042],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002776212,0.0007444809,0.4492198,0.001032532,0.001563999,0.000647266,0.4657979,0.05813005,0.0200878],"genre_scores_gemma":[0.0179016,0.0008083677,0.5872676,0.0007484147,0.0003283904,0.001819899,0.3472735,0.0259138,0.01793843],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5658749,"threshold_uncertainty_score":0.6192268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07751403345104468,"score_gpt":0.3905209171662954,"score_spread":0.3130068837152508,"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."}}