{"id":"W6884863288","doi":"10.12927/cjnl.2019.25964\">10.12927/cjnl.2019.25964</a></p","title":"Big Data: Why Should Canadian Nurse Leaders Care?","year":2019,"lang":"en","type":"article","venue":"Scholar Commons (University of South Carolina)","topic":"Nursing Diagnosis and Documentation","field":"Nursing","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Big data; Health care; Health informatics; Informatics; Health Administration Informatics; Perspective (graphical); Field (mathematics); Analytics; Data governance","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01483962,0.0004583994,0.0006097424,0.002342688,0.02169364,0.01686035,0.003707848,0.006113573,0.01396184],"category_scores_gemma":[0.07365961,0.0005457066,0.0007244957,0.006364933,0.0110487,0.008665657,0.008421694,0.009763132,0.002160975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.09257609,"about_ca_system_score_gemma":0.3173085,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9257951,"about_ca_topic_score_gemma":0.9638993,"domain_scores_codex":[0.9849142,0.003382467,0.0007578035,0.001169067,0.006149113,0.003627324],"domain_scores_gemma":[0.9308785,0.009567854,0.002941933,0.002166171,0.02757931,0.02686624],"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":[0.00009235698,0.00005851674,0.01887645,0.0006054594,0.0000440791,0.0005360031,0.01556962,0.0001646287,0.0001865618,0.02901701,0.8210078,0.1138415],"study_design_scores_gemma":[0.0001002237,0.00005578098,0.02772163,0.003538213,0.00006066784,0.0002952754,0.08352822,0.0005090854,0.00026006,0.02738094,0.8562966,0.0002532525],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.006473131,0.00536295,0.0004922493,0.9684816,0.003218949,0.00005258722,0.0006310488,0.00006312416,0.01522438],"genre_scores_gemma":[0.3499809,0.03460024,0.007489317,0.5628252,0.004746125,0.0003285205,0.002550059,0.0004439002,0.03703579],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.09257609,"threshold_uncertainty_score":0.6716897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05886586943236971,"score_gpt":0.268572098000269,"score_spread":0.2097062285678993,"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."}}