{"id":"W2038814013","doi":"10.1016/j.jopan.2007.12.004","title":"Prognostic Models and Risk Scores: Can We Accurately Predict Postoperative Nausea and Vomiting in Children after Craniotomy?","year":2008,"lang":"en","type":"article","venue":"Journal of PeriAnesthesia Nursing","topic":"Nausea and vomiting management","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta; Alberta Health Services","funders":"","keywords":"Postoperative nausea and vomiting; Craniotomy; Nausea; Medicine; Vomiting; Context (archaeology); Population; Adverse effect; Risk assessment; Intensive care medicine; Physical therapy; Medical physics; Surgery; Computer science; Internal medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.004311837,0.001089177,0.001369091,0.001076747,0.0003706123,0.001660705,0.0008890146,0.001267916,0.001214332],"category_scores_gemma":[0.03923278,0.0002955702,0.0009405544,0.001035822,0.0004600581,0.002501506,0.0007604003,0.002401252,0.0003961854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005214546,"about_ca_system_score_gemma":0.001474743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003587163,"about_ca_topic_score_gemma":0.004634337,"domain_scores_codex":[0.9986905,0.0006268594,0.0001942123,0.0001136306,0.0002546253,0.0001201255],"domain_scores_gemma":[0.9880212,0.007399575,0.002501184,0.0005142692,0.0008803348,0.0006834841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003800256,0.00008190508,0.9772812,0.00003884112,0.0001248722,0.00008330675,0.00006599799,0.001570666,0.00007133614,0.0002361149,0.0007425738,0.01932317],"study_design_scores_gemma":[0.0002368097,0.002136997,0.8788498,0.0004532815,0.0008919657,0.001601879,0.001287053,0.103611,0.0007756905,0.007037498,0.003002477,0.0001155689],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9748272,0.005641123,0.009930039,0.005619498,0.0003032229,0.00007544893,0.00122334,0.0000919609,0.002288266],"genre_scores_gemma":[0.9919477,0.001514159,0.005185034,0.0001783577,0.0001494382,0.00003899782,0.0007999853,0.00001673075,0.0001695472],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004311837,"threshold_uncertainty_score":0.02280349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02463504368538751,"score_gpt":0.2726657790086293,"score_spread":0.2480307353232417,"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."}}