{"id":"W2567139073","doi":"10.1080/09332480.2001.10542253","title":"On the Edge: Statistics & Computing","year":2001,"lang":"en","type":"article","venue":"CHANCE","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Enhanced Data Rates for GSM Evolution; Computer science; 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":[0.004671615,0.001832399,0.002588852,0.003396081,0.001747039,0.009603831,0.001960828,0.00320827,0.04854634],"category_scores_gemma":[0.03743495,0.001619189,0.0009318544,0.007821123,0.006340997,0.01531057,0.00406116,0.008586963,0.02800818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001573884,"about_ca_system_score_gemma":0.002452831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003688715,"about_ca_topic_score_gemma":0.005156153,"domain_scores_codex":[0.9951357,0.002507312,0.0003430897,0.0005616562,0.001286682,0.0001656246],"domain_scores_gemma":[0.9775282,0.0156705,0.0005390178,0.002861549,0.00224117,0.001159559],"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":[0.00009160792,0.00004972331,0.0008827261,0.0005103086,0.0000479037,0.0001195155,0.0003541387,0.002045113,0.0005244648,0.3976997,0.3748975,0.2227772],"study_design_scores_gemma":[0.00003242811,0.00002736623,0.0004773994,0.000263488,0.00002899116,0.0002041674,0.0001585285,0.01552729,0.000518839,0.6024654,0.3802471,0.00004892336],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.001540731,0.0359989,0.8517775,0.02077394,0.007341075,0.00008944693,0.001112982,0.01268492,0.0686806],"genre_scores_gemma":[0.09588587,0.03660653,0.7084625,0.0145214,0.01602131,0.0008724164,0.003526626,0.01270899,0.1113945],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.04854634,"threshold_uncertainty_score":0.1624037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03400462124648552,"score_gpt":0.2902844776059227,"score_spread":0.2562798563594372,"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."}}