{"id":"W3117348517","doi":"10.1089/big.2020.29039.cfp2","title":"<i>Call for Special Issue Papers:</i> Programming Models and Algorithms for Big Data","year":2020,"lang":"en","type":"article","venue":"Big Data","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Big data; Computer science; Data science; Analytics; World Wide Web; Data mining","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":[0.0004426985,0.0002551109,0.0002989947,0.00006777055,0.0002476248,0.0007670323,0.002303902,0.0001015438,0.00004161394],"category_scores_gemma":[0.0005518841,0.0002284973,0.00003496886,0.0003389282,0.00008991543,0.002563325,0.003205797,0.0001014606,0.00005778892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006076568,"about_ca_system_score_gemma":0.00004006162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001858159,"about_ca_topic_score_gemma":0.0002265135,"domain_scores_codex":[0.9979121,0.000004805474,0.0003380774,0.001076162,0.0002416665,0.0004271732],"domain_scores_gemma":[0.9980948,0.00008810403,0.0001680918,0.001472043,0.0001357261,0.00004121614],"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":[0.00008449582,0.00004218512,0.00004538133,0.0004490097,0.00002404008,0.000002518739,0.00001744254,0.000004908643,0.00006484249,0.0005888551,0.3140001,0.6846762],"study_design_scores_gemma":[0.0005162817,0.00001633927,0.00002026763,0.00004488431,0.0001181436,0.000001482909,0.00007386818,0.1074049,0.00002467335,0.0004556294,0.8910281,0.000295448],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"editorial","genre_scores_codex":[0.0005133129,0.00171846,0.9130889,0.0376524,0.01087931,0.005736113,0.02200232,0.0006568697,0.007752372],"genre_scores_gemma":[0.04687019,0.001210501,0.09704708,0.0371174,0.6248295,0.0005050638,0.1901356,0.0004645639,0.00182012],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8160418,"threshold_uncertainty_score":0.931785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4013043329561768,"score_gpt":0.340158165246507,"score_spread":0.06114616770966974,"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."}}