{"id":"W2367630464","doi":"","title":"Study of medical effectiveness of provincial stroke care delivery:based on Logistic regression","year":2014,"lang":"en","type":"article","venue":"Journal of Guangzhou University","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Logistic regression; Inflection point; Regression analysis; Statistics; Stroke (engine); Regression; Segmented regression; Medicine; Econometrics; Mathematics; Engineering; Nonlinear regression","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":[0.01379183,0.0004710082,0.0009673646,0.002118284,0.0005736762,0.00153972,0.001993363,0.000569849,0.002878974],"category_scores_gemma":[0.09013837,0.0002877783,0.002217354,0.004055944,0.0006769623,0.001534535,0.001026784,0.001437128,0.0002472588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003844649,"about_ca_system_score_gemma":0.004187804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1200518,"about_ca_topic_score_gemma":0.04192848,"domain_scores_codex":[0.9842929,0.01002443,0.000835374,0.001287523,0.002566934,0.0009928356],"domain_scores_gemma":[0.8990882,0.08372118,0.009605774,0.002063425,0.004200564,0.001320798],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004717924,0.0002358315,0.9576777,0.0002009306,0.00160039,0.0003238303,0.0008280692,0.01910954,0.0001482775,0.002425694,0.000679532,0.01629852],"study_design_scores_gemma":[0.00005256103,0.0008531437,0.7525218,0.00009589102,0.001167633,0.0002904134,0.002014098,0.2394739,0.0003719195,0.001456966,0.001648626,0.00005304183],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9835628,0.0007416709,0.009920088,0.00104507,0.00002919119,0.0001481883,0.001040849,0.00006312763,0.003449029],"genre_scores_gemma":[0.9974309,0.0001201291,0.001560307,0.0000226017,0.00001424076,0.00003723726,0.0003173518,0.0000116947,0.0004855156],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1200518,"threshold_uncertainty_score":0.2387061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.112343878237889,"score_gpt":0.4441245728425358,"score_spread":0.3317806946046468,"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."}}