{"id":"W4394210831","doi":"10.6084/m9.figshare.22603159","title":"Additional file 5 of Plasma lipidomic profiling reveals metabolic adaptations to pregnancy and signatures of cardiometabolic risk: a preconception and longitudinal cohort study","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"Birth, Development, and Health","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Profiling (computer programming); Cohort; Pregnancy; Medicine; Metabolic syndrome; Obstetrics; Computational biology; Bioinformatics; Internal medicine; Biology; Genetics; Computer science; Obesity","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001732324,0.001677797,0.00178864,0.001639196,0.001096263,0.002172125,0.002306692,0.002254447,0.3783734],"category_scores_gemma":[0.019301,0.0007787843,0.002218473,0.003259426,0.0002897735,0.001165863,0.001495708,0.001371342,0.05436315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001095447,"about_ca_system_score_gemma":0.00210871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02006531,"about_ca_topic_score_gemma":0.03533083,"domain_scores_codex":[0.9989661,0.0002132487,0.0001952302,0.0003479213,0.0001185869,0.000158958],"domain_scores_gemma":[0.9929746,0.004076281,0.0007013003,0.0009295598,0.0009864283,0.0003318255],"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":[0.0008680087,0.0000936216,0.01532292,0.005776384,0.0004647457,0.0001205128,0.0001006695,0.0006481149,0.0002542376,0.0006434755,0.9699939,0.005713474],"study_design_scores_gemma":[0.01077953,0.0004816558,0.1110814,0.006662563,0.001769312,0.0007563967,0.0005508306,0.002205816,0.001030279,0.007090331,0.8573115,0.0002802878],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001987728,0.00003402507,0.00007414011,0.00005226197,0.00001185574,0.00002639942,0.9993994,0.00005524214,0.0001478263],"genre_scores_gemma":[0.004505989,0.0001290752,0.001256374,0.0003267833,0.00004577235,0.001136881,0.9900653,0.0001393188,0.002394614],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3783734,"threshold_uncertainty_score":0.8866749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04467314314038575,"score_gpt":0.3101587495580445,"score_spread":0.2654856064176588,"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."}}