{"id":"W4413893866","doi":"10.4081/cardio.2025.80","title":"Lipoprotein(a): what clinicians need to know","year":2025,"lang":"en","type":"article","venue":"Global Cardiology","topic":"Lipoproteins and Cardiovascular Health","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Need to know; Medicine; Intensive care medicine; Computer science; Computer security","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007003898,0.0002110462,0.0009397965,0.00009958877,0.00009810177,0.00003611075,0.000168712,0.0003095522,0.00003117773],"category_scores_gemma":[0.0002683495,0.0001842425,0.0006047692,0.000644612,0.00008219716,0.00007384746,0.0001544933,0.0002362646,0.000353637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002969609,"about_ca_system_score_gemma":0.0003856137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004075227,"about_ca_topic_score_gemma":0.00006153346,"domain_scores_codex":[0.998086,0.0002020242,0.0003759904,0.0005199621,0.0002590129,0.0005569615],"domain_scores_gemma":[0.9984962,0.00002878138,0.00003947421,0.000965612,0.0001913011,0.000278669],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006900779,0.00006641103,0.01640491,0.0002020563,0.001148803,0.0004426393,0.00004428452,0.0001187398,0.0002137435,0.007109592,0.1261631,0.8473957],"study_design_scores_gemma":[0.001930919,0.0005992181,0.07649563,0.0002548102,0.0003503275,0.0004445837,0.0005589818,0.00001077925,0.0002115726,0.001369719,0.9175476,0.0002257835],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4905168,0.05380308,0.02845636,0.08423506,0.01018856,0.006024554,0.00009024721,0.000774364,0.325911],"genre_scores_gemma":[0.9751447,0.001612859,0.001302881,0.0186911,0.001508796,0.0001844609,0.00003473344,0.00001874867,0.001501656],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8471699,"threshold_uncertainty_score":0.7513193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01163491723735739,"score_gpt":0.3144226758901416,"score_spread":0.3027877586527842,"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."}}