{"id":"W4387497240","doi":"10.1136/rapm-2023-esra.678","title":"#37207 Improving outcomes in postpartum haemorrhage: recognition and resuscitation","year":2023,"lang":"en","type":"article","venue":"","topic":"Maternal and fetal healthcare","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Resuscitation; Postpartum haemorrhage; Computer science; Intensive care medicine; Medicine; Pregnancy; Emergency medicine","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":[0.002755262,0.0004443524,0.0006624394,0.001046415,0.001259473,0.002647286,0.001150911,0.003076238,0.05633386],"category_scores_gemma":[0.02686987,0.0002102031,0.0007471172,0.0006563675,0.0008494419,0.002211634,0.003041383,0.004774742,0.01699631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002617116,"about_ca_system_score_gemma":0.006093038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004716446,"about_ca_topic_score_gemma":0.006735432,"domain_scores_codex":[0.9976339,0.0009380115,0.0003452177,0.0001548682,0.0005811302,0.0003469048],"domain_scores_gemma":[0.98847,0.0028175,0.001289165,0.0003016153,0.003910921,0.003210895],"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":[0.00007936503,0.00009330079,0.003997118,0.001305609,0.0000293601,0.0003057886,0.0002610529,0.0001351879,0.00009081455,0.002581206,0.7284279,0.2626933],"study_design_scores_gemma":[0.0001837022,0.0005742766,0.04261529,0.03218792,0.00009597719,0.002317904,0.002454348,0.0006176308,0.0003348384,0.01384975,0.9046681,0.0001003163],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.005374552,0.09119196,0.002943267,0.7478388,0.03277758,0.0005678995,0.001758336,0.0007143985,0.1168331],"genre_scores_gemma":[0.1207893,0.4561026,0.02057315,0.2361387,0.1066819,0.002118306,0.004794413,0.0007275883,0.05207407],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.05633386,"threshold_uncertainty_score":0.1884555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06041728966412922,"score_gpt":0.3229766764377592,"score_spread":0.26255938677363,"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."}}