{"id":"W2393764988","doi":"","title":"The Reason Analysis of Influencing Network Data Current Capacity","year":2009,"lang":"en","type":"article","venue":"China Printing and Packaging Study","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Character (mathematics); Flow (mathematics); Similarity (geometry); Set (abstract data type); Network analysis; Flow network; Computer science; Data mining; Artificial intelligence; Mathematics; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001806943,0.0001188018,0.0002415711,0.00006140587,0.0004953295,0.0002002516,0.0009092866,0.00001682676,3.831099e-7],"category_scores_gemma":[0.0001069045,0.00008356175,0.00004593237,0.0008287454,0.00003627988,0.0001734981,0.0003374569,0.0002034891,5.581991e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009080612,"about_ca_system_score_gemma":0.00002071343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003624816,"about_ca_topic_score_gemma":0.00004542255,"domain_scores_codex":[0.9986654,0.0001661226,0.0003048198,0.0003970181,0.0002109041,0.0002557537],"domain_scores_gemma":[0.9984416,0.0002141672,0.0001976946,0.001045071,0.00004877018,0.00005271843],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000002755272,0.00005756296,0.182643,0.000002340033,0.0001626404,8.204953e-7,0.001608903,0.002748743,0.000002482358,0.004070558,0.00005380453,0.8086464],"study_design_scores_gemma":[0.0001538657,0.00003869301,0.6969836,0.00002462229,0.0001892745,8.391052e-7,0.00009298815,0.3016775,0.000001186179,0.0004422358,0.0003081638,0.00008707948],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9288657,0.001250607,0.06875186,0.0004419148,0.0002148389,0.0001690027,0.000001055281,0.00009950721,0.0002055004],"genre_scores_gemma":[0.9991133,0.00006120691,0.0006754844,0.00003319739,0.0001019941,0.000002277246,0.000001484614,0.000002625007,0.000008470518],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8085594,"threshold_uncertainty_score":0.3809724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02904258786118149,"score_gpt":0.2811429341444533,"score_spread":0.2521003462832718,"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."}}