{"id":"W4391225823","doi":"10.3991/ijet.v19i02.47229","title":"10.3991/ijet.v19i02.47229","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Augment; Mode (computer interface); Computer science; Big data; Deep learning; Data science; Artificial intelligence; Human–computer interaction; Data mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000793435,0.0009087932,0.0006750276,0.002833384,0.00112489,0.005100022,0.001151152,0.002716099,0.921273],"category_scores_gemma":[0.002180543,0.0004474822,0.0006931845,0.003714525,0.0008117313,0.002765764,0.002124526,0.001396894,0.8900533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008213017,"about_ca_system_score_gemma":0.0009055932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001975812,"about_ca_topic_score_gemma":0.001572437,"domain_scores_codex":[0.9994742,0.00008191873,0.0000534498,0.0001095946,0.0001704288,0.0001103757],"domain_scores_gemma":[0.9985525,0.0004524983,0.00008755257,0.000303224,0.0002601226,0.0003440022],"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":[0.0003748768,0.0005933595,0.004049561,0.0005007458,0.00002762446,0.0003878444,0.0001176435,0.00131797,0.002830312,0.00940359,0.2616757,0.7187209],"study_design_scores_gemma":[0.00008011574,0.0001343333,0.003532311,0.0004466086,0.00002274945,0.001121661,0.0003290144,0.00244206,0.001784786,0.00558059,0.9844891,0.00003676525],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.004395973,0.001159291,0.004355828,0.001362191,0.001382402,0.00009202074,0.003224551,0.001556749,0.982471],"genre_scores_gemma":[0.01858237,0.0009388783,0.002995519,0.0004585565,0.0003282989,0.00006426288,0.003136378,0.0005770376,0.9729187],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.07872701,"threshold_uncertainty_score":0.1122944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02718348118485296,"score_gpt":0.21686085197234,"score_spread":0.1896773707874871,"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."}}