{"id":"W6902114434","doi":"10.6084/m9.figshare.19101786","title":"Additional file 1 of The path from big data analytics capabilities to value in hospitals: a scoping review","year":2022,"lang":"en","type":"article","venue":"Open MIND","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Big data; Path (computing); Value (mathematics); Analytics; Data analysis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006097496,0.001219842,0.001818406,0.008881977,0.0009176268,0.002334857,0.002043041,0.001845696,0.820132],"category_scores_gemma":[0.09506966,0.0007097759,0.002073814,0.01450126,0.0004562602,0.003907922,0.001937637,0.001465446,0.05764778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003119937,"about_ca_system_score_gemma":0.008412461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01042793,"about_ca_topic_score_gemma":0.01703278,"domain_scores_codex":[0.9970307,0.0006355321,0.001049168,0.0004077433,0.0006328365,0.0002440637],"domain_scores_gemma":[0.8838223,0.09528411,0.006935519,0.001629781,0.01135149,0.0009767894],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0004463151,0.0000585035,0.001182151,0.1121592,0.0001750409,0.00007527906,0.0002035238,0.0003240997,0.0000933815,0.002822927,0.8668486,0.01561092],"study_design_scores_gemma":[0.004423101,0.0002761439,0.01582576,0.1049033,0.001085196,0.0003518937,0.001010701,0.0007666211,0.0004431357,0.01240533,0.85833,0.0001788121],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000129658,0.0002814649,0.00020518,0.0004922504,0.00005784593,0.0005251269,0.9968676,0.00007784192,0.001362893],"genre_scores_gemma":[0.009854342,0.004680053,0.009749716,0.0031447,0.0004472837,0.0308129,0.9140008,0.0004684789,0.02684173],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.820132,"threshold_uncertainty_score":0.25656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.394183956416131,"score_gpt":0.503247005097594,"score_spread":0.109063048681463,"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."}}