{"id":"W81184795","doi":"10.1007/978-3-642-22351-8_5","title":"Using Medians to Generate Consensus Rankings for Biological Data","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Ranking (information retrieval); Computer science; Heuristic; Set (abstract data type); Permutation (music); Information retrieval; Data mining; Theoretical computer science; Artificial intelligence","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":[0.01292947,0.001743552,0.002860831,0.00754165,0.002229143,0.003295579,0.0034081,0.002035974,0.005333326],"category_scores_gemma":[0.03576371,0.001185411,0.002742277,0.004759607,0.001079493,0.003443108,0.003533416,0.002684728,0.002583261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001937113,"about_ca_system_score_gemma":0.002505845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003664875,"about_ca_topic_score_gemma":0.00660557,"domain_scores_codex":[0.992733,0.002584907,0.0005824746,0.001336707,0.002293925,0.0004689051],"domain_scores_gemma":[0.980372,0.0114673,0.0008492948,0.002357129,0.004338075,0.00061619],"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":[0.0008586707,0.0003330153,0.007226454,0.000650281,0.0008979563,0.0002167307,0.000610306,0.181762,0.008575353,0.02542981,0.02878625,0.7446532],"study_design_scores_gemma":[0.0001441811,0.0002077771,0.001449954,0.00006339357,0.0001002704,0.0001056458,0.0002902991,0.8773212,0.005715267,0.1095791,0.004952678,0.00007028179],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02293416,0.0004945248,0.9690998,0.0002823447,0.0002156049,0.0002099214,0.001082334,0.004119074,0.001562184],"genre_scores_gemma":[0.1864694,0.0002283108,0.8027865,0.0001853571,0.0002051469,0.0004926851,0.006502179,0.0009160902,0.002214264],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01292947,"threshold_uncertainty_score":0.06837839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1746587259477483,"score_gpt":0.3131925044327062,"score_spread":0.138533778484958,"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."}}