{"id":"W2545943971","doi":"10.1145/2837060.2837072","title":"FIMaaS","year":2015,"lang":"en","type":"article","venue":"","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Popularity; Scalability; Variety (cybernetics); Data science; Big data; Service (business); Schedule; Cloud computing; Knowledge extraction; World Wide Web; Data mining; Database; Business; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001688943,0.001771141,0.001287856,0.003152713,0.001617871,0.005009583,0.004196746,0.00236511,0.2444423],"category_scores_gemma":[0.008414421,0.0008654432,0.001467532,0.003017735,0.0006532494,0.006668157,0.004116664,0.002358073,0.2279339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001216393,"about_ca_system_score_gemma":0.002289797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003467237,"about_ca_topic_score_gemma":0.002616204,"domain_scores_codex":[0.9977638,0.0002249434,0.0001623043,0.0004943216,0.000966724,0.0003877999],"domain_scores_gemma":[0.9966409,0.0005159038,0.0002002271,0.001292386,0.0008803493,0.0004702523],"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":[0.0008215266,0.0002120501,0.001569146,0.0004493847,0.00006978794,0.0004354133,0.0001777405,0.001752623,0.005485241,0.03175846,0.639143,0.3181255],"study_design_scores_gemma":[0.0001009427,0.00006303449,0.000756823,0.00008645301,0.00002487421,0.0005372655,0.00005473299,0.00973932,0.00318623,0.01471769,0.9706835,0.00004909651],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.007627598,0.00264742,0.1959636,0.00493624,0.002655432,0.001176039,0.04038922,0.3254615,0.4191429],"genre_scores_gemma":[0.09761816,0.004441518,0.2566497,0.004589247,0.001310959,0.001846056,0.1583063,0.02851743,0.4467207],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7555577,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06047956322618069,"score_gpt":0.2758004244980998,"score_spread":0.2153208612719191,"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."}}