{"id":"W2315915688","doi":"10.1103/physreve.89.012709","title":"Maximum likelihood estimators for truncated and censored power-law distributions show how neuronal avalanches may be misevaluated","year":2014,"lang":"en","type":"article","venue":"Physical Review E","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Estimator; Power law; Statistical physics; Range (aeronautics); Bounded function; Distribution (mathematics); Law; Power (physics); Probability distribution; Computer science; Econometrics; Physics; Mathematics; Statistics; Mathematical analysis; Quantum mechanics; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01964658,0.001147111,0.001378703,0.002759711,0.0004975233,0.002749562,0.003487124,0.002527969,0.001950146],"category_scores_gemma":[0.1270969,0.0009084308,0.001123705,0.002262214,0.003864406,0.006218136,0.001791049,0.003091038,0.0006536769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001465283,"about_ca_system_score_gemma":0.0008459375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001645868,"about_ca_topic_score_gemma":0.001290756,"domain_scores_codex":[0.9945899,0.00343791,0.0002963067,0.0007624715,0.0007634141,0.0001499906],"domain_scores_gemma":[0.9028986,0.08599182,0.004172049,0.004509441,0.002146933,0.0002811886],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009082474,0.00007015206,0.01218368,0.0007468714,0.0004282239,0.0003837685,0.000614533,0.4402457,0.002135781,0.4003473,0.002794703,0.1399584],"study_design_scores_gemma":[0.00002858859,0.00005324707,0.003297157,0.0002230197,0.00004142427,0.000297533,0.00008899076,0.6050475,0.001717729,0.3860506,0.003066598,0.00008763272],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006173407,0.0007342727,0.9919066,0.0002880846,0.00002948696,0.00002080069,0.00006540694,0.0001633971,0.0006185402],"genre_scores_gemma":[0.4071957,0.003681592,0.5837709,0.0006081644,0.0002969451,0.0003694837,0.0007317299,0.0003765408,0.002968939],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01964658,"threshold_uncertainty_score":0.1039023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03306588302069971,"score_gpt":0.3019544338610706,"score_spread":0.2688885508403709,"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."}}