{"id":"W1991704078","doi":"10.1016/j.jcss.2012.05.001","title":"Special issue: Frontiers and advance topics of computer and information technology","year":2012,"lang":"en","type":"article","venue":"Journal of Computer and System Sciences","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Computer science; Data science; Information technology; Library science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004382263,0.00006859106,0.0001887156,0.0002953376,0.00009627315,0.0001819653,0.0001517677,0.00003822228,0.000004625801],"category_scores_gemma":[0.000008512061,0.00004749513,0.00001507745,0.0002454637,0.0001922839,0.00389461,0.0001259832,0.0000551431,0.000002022929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004933367,"about_ca_system_score_gemma":0.000008928011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006270653,"about_ca_topic_score_gemma":7.25723e-7,"domain_scores_codex":[0.9993458,0.000005757669,0.0003025127,0.00006026838,0.0001723026,0.0001133293],"domain_scores_gemma":[0.9994333,0.00001350406,0.000353778,0.00004718619,0.0001379932,0.00001427706],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002617235,0.0000290875,0.1985185,0.0007207954,0.00002287185,0.000002502355,0.0004175742,0.00006115452,0.00001348644,0.04187161,0.02263292,0.7356833],"study_design_scores_gemma":[0.0005356587,0.000128797,0.08517659,0.0005534813,0.00005129951,0.000364734,0.001830899,0.02867813,0.00006310031,0.0008079332,0.8815544,0.0002549436],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6727679,0.003186969,0.3055066,0.002312125,0.01065327,0.0002062896,0.000003171733,0.00002781546,0.00533586],"genre_scores_gemma":[0.9650094,0.0001629033,0.022383,0.0002641348,0.01216026,3.615121e-7,6.619107e-7,0.000002532153,0.00001675512],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8589215,"threshold_uncertainty_score":0.2823498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02023050610696172,"score_gpt":0.2495310835032312,"score_spread":0.2293005773962695,"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."}}