{"id":"W2123255899","doi":"10.1080/09332480.2001.10542284","title":"On the Edge: Statistics & Computing","year":2001,"lang":"en","type":"article","venue":"CHANCE","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Computational statistics; 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":[0.002355402,0.002407379,0.002395975,0.004741332,0.00132282,0.00571834,0.002567476,0.001794976,0.2930925],"category_scores_gemma":[0.04149674,0.002034107,0.001196037,0.006189484,0.001276327,0.006041265,0.003630534,0.004817901,0.2539374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001051289,"about_ca_system_score_gemma":0.002721331,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003376897,"about_ca_topic_score_gemma":0.006254256,"domain_scores_codex":[0.9981694,0.000302992,0.0001716936,0.0003305796,0.0008206845,0.0002046119],"domain_scores_gemma":[0.9834597,0.007650021,0.0007079132,0.003271267,0.003156737,0.001754401],"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":[0.0001210136,0.00006152363,0.0007271271,0.0002286936,0.0000216117,0.00008011593,0.00006214967,0.0004939004,0.001286712,0.007757837,0.8214908,0.1676684],"study_design_scores_gemma":[0.0003695184,0.0001420741,0.004114195,0.0004431917,0.00008731524,0.0004465286,0.0001631463,0.04013096,0.02022353,0.1565556,0.7770677,0.0002562556],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"commentary","genre_scores_codex":[0.003794131,0.001288978,0.5826116,0.007103742,0.00290355,0.0007670809,0.0291354,0.2745404,0.09785507],"genre_scores_gemma":[0.03485967,0.001725835,0.6876559,0.005147024,0.001938457,0.001938242,0.03419894,0.08011813,0.1524178],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.2930925,"threshold_uncertainty_score":0.9804919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04397246498573638,"score_gpt":0.2906903123048136,"score_spread":0.2467178473190772,"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."}}