{"id":"W601140154","doi":"10.46298/dmtcs.2788","title":"The height of scaled attachment random recursive trees","year":2010,"lang":"en","type":"article","venue":"Discrete Mathematics & Theoretical Computer Science","topic":"Stochastic processes and statistical mechanics","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Combinatorics; Mathematics; Bounded function; Random walk; Preferential attachment; Random tree; Sequence (biology); Random variable; Tree (set theory); Random graph; Discrete mathematics; Random binary tree; Class (philosophy); Branching (polymer chemistry); Binary logarithm; Binary tree; Mathematical analysis; Statistics; Graph; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002489465,0.0002757396,0.0004913988,0.00007589012,0.0006061111,0.0002222523,0.001536447,0.00008830211,0.000142177],"category_scores_gemma":[0.003150261,0.0001553569,0.0001532033,0.0004382015,0.004030714,0.000114039,0.0005034257,0.0003861194,0.00002661415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001997012,"about_ca_system_score_gemma":0.000109178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.726746e-7,"about_ca_topic_score_gemma":0.000004508132,"domain_scores_codex":[0.99703,0.00006125088,0.0007417835,0.0004433103,0.001110379,0.0006133074],"domain_scores_gemma":[0.9927856,0.005290841,0.0002901854,0.0009296701,0.0004290849,0.0002746629],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003963598,0.0001221163,0.000002042516,0.00006988321,0.000018815,0.000003190532,0.0007163454,0.000001801241,0.001101352,0.994752,0.00008601302,0.003086799],"study_design_scores_gemma":[0.0004538743,0.0001630004,0.00001017785,0.00007865737,0.00005106572,0.00002373403,0.0001084417,0.1695183,0.00380454,0.825563,0.00004535091,0.0001798027],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01556802,0.00002277641,0.9782708,0.0006053332,0.0006104857,0.0004795902,0.00001836426,0.00006176929,0.004362825],"genre_scores_gemma":[0.6557866,0.00000603971,0.3440173,0.00003963444,0.00008465233,0.0000247094,8.398071e-7,0.00001846761,0.00002184766],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6402186,"threshold_uncertainty_score":0.9986798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01497497168242136,"score_gpt":0.3028794344697585,"score_spread":0.2879044627873372,"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."}}