{"id":"W4226168992","doi":"10.3390/books978-3-0365-3192-2","title":"Big Data Analytics and Information Science for Business and Biomedical Applications","year":2022,"lang":"en","type":"book","venue":"","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Science and Technology Planning Project of Guangdong Province; Natural Sciences and Engineering Research Council of Canada; Ministry of Science and ICT, South Korea; People's Government of Jilin Province; National Research Foundation of Korea; National Institutes of Health; Canada Research Chairs; National Research Foundation; University of Cincinnati; National Natural Science Foundation of China; Compute Canada; National Science Foundation","keywords":"Big data; Data science; Computer science; Analytics; Business analytics; Data analysis; Business model; Data mining; Business analysis; Business; Marketing","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001145553,0.001649323,0.001121078,0.003165485,0.001094406,0.008587942,0.001386838,0.001923615,0.03413577],"category_scores_gemma":[0.004055449,0.0007573319,0.0009446271,0.008074849,0.001899675,0.007957063,0.002760865,0.00428977,0.02596137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001229809,"about_ca_system_score_gemma":0.002311302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001368395,"about_ca_topic_score_gemma":0.002755451,"domain_scores_codex":[0.998318,0.0002317277,0.00005896679,0.0001547308,0.001170626,0.00006615086],"domain_scores_gemma":[0.9979703,0.001298941,0.00008290436,0.0001835825,0.000328715,0.0001355298],"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":[0.00002014998,0.00002140679,0.0001109659,0.0005689313,0.00003498081,0.00006572315,0.0002047788,0.0006147542,0.0005625954,0.1023618,0.7651415,0.1302924],"study_design_scores_gemma":[0.000003776848,0.000007955176,0.0002334385,0.000218133,0.000005313992,0.0001270992,0.0000549465,0.0006223253,0.0001135232,0.05158453,0.9470177,0.0000112544],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001491246,0.2427389,0.09178287,0.03202524,0.02173463,0.0003672817,0.005251601,0.003091622,0.6015165],"genre_scores_gemma":[0.01101852,0.1484266,0.0770907,0.01283163,0.01024147,0.0005004703,0.005625938,0.002022247,0.7322424],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.03413577,"threshold_uncertainty_score":0.1141955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1269445460174874,"score_gpt":0.3066093207363693,"score_spread":0.1796647747188819,"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."}}