{"id":"W2561054455","doi":"10.1080/09332480.2000.10542208","title":"On the Edge: Statistics &amp; Computing","year":2000,"lang":"en","type":"article","venue":"CHANCE","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Enhanced Data Rates for GSM Evolution; Statistics; Mathematics; 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":[0.004770259,0.001580504,0.002979122,0.00426072,0.001852009,0.009133458,0.002218366,0.003527342,0.02135172],"category_scores_gemma":[0.04043169,0.001145236,0.0009494817,0.01069917,0.007619587,0.01795125,0.004358069,0.00853783,0.01083564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00203303,"about_ca_system_score_gemma":0.002458544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002816008,"about_ca_topic_score_gemma":0.002471304,"domain_scores_codex":[0.9955427,0.002171736,0.0002730503,0.0006897128,0.001134203,0.0001885649],"domain_scores_gemma":[0.9725783,0.02032355,0.0008824393,0.002638511,0.002296897,0.001280233],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008254997,0.00003856331,0.001138385,0.000437784,0.00005192834,0.000114368,0.0001712687,0.003002633,0.0002494645,0.6159709,0.1620772,0.2166649],"study_design_scores_gemma":[0.00001566843,0.00001853376,0.0002470204,0.000150923,0.00001954539,0.0001245686,0.00006124398,0.01396898,0.00020533,0.8991773,0.08598599,0.00002494628],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"commentary","genre_scores_codex":[0.002996055,0.06985709,0.8138455,0.0516935,0.008495977,0.00007560096,0.0009473297,0.003572936,0.04851612],"genre_scores_gemma":[0.2076907,0.07988325,0.5797029,0.0253518,0.03671509,0.0007591026,0.002364479,0.003933246,0.06359948],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.02135172,"threshold_uncertainty_score":0.07142866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02965125121622192,"score_gpt":0.2742322750065523,"score_spread":0.2445810237903304,"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."}}