{"id":"W2902964569","doi":"10.1016/j.artres.2018.10.212","title":"P159 CORRELATION BETWEEN INFLAMMATORY STATE AND ARTERIAL STIFFNESS","year":2018,"lang":"en","type":"article","venue":"Artery Research","topic":"Cardiac, Anesthesia and Surgical Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Arterial stiffness; Cardiology; State (computer science); Internal medicine; Blood pressure; Algorithm","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":[0.0003250696,0.0002780739,0.0002568029,0.0006727518,0.0002747128,0.0005173092,0.000236628,0.0003696809,0.03603589],"category_scores_gemma":[0.002578548,0.0001179507,0.0003118267,0.001032189,0.0002219467,0.0002807241,0.0003397878,0.0005365415,0.003338263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000115183,"about_ca_system_score_gemma":0.0004030665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007795455,"about_ca_topic_score_gemma":0.0006227719,"domain_scores_codex":[0.9996035,0.000102195,0.00004282184,0.00008871564,0.0001115109,0.00005136093],"domain_scores_gemma":[0.9991705,0.0003149408,0.0002368857,0.00003557043,0.0001408732,0.0001011039],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001001887,0.0001872242,0.9419759,0.0004348795,0.0002428955,0.0008756117,0.000225256,0.00009645218,0.001197661,0.0003685873,0.01059813,0.04279546],"study_design_scores_gemma":[0.00004100897,0.0003236427,0.9853964,0.0001536739,0.0001188164,0.00234644,0.000223026,0.0004826136,0.0003031262,0.0006724104,0.009927584,0.00001110011],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9433927,0.01047221,0.002525817,0.002498556,0.00096788,0.0001364893,0.01014141,0.0001334259,0.02973155],"genre_scores_gemma":[0.9903565,0.001328742,0.0009739614,0.0001860847,0.0004427192,0.00007714396,0.001894072,0.00001804123,0.004722741],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03603589,"threshold_uncertainty_score":0.1205521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05939181371904557,"score_gpt":0.3636273767284411,"score_spread":0.3042355630093955,"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."}}