{"id":"W6904028897","doi":"10.1371/journal.pcbi.1007882.g005","title":"Forest plots for associations between proteins under genetic control and clinical parameters.","year":2020,"lang":"en","type":"other","venue":"Figshare","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Confidence interval; Selection (genetic algorithm); Body mass index; Genetic variants; Linear regression; Genetic variation; Interval (graph theory)","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":[0.003799937,0.001587642,0.001379502,0.004721458,0.000955955,0.001510796,0.001104334,0.001226651,0.1078273],"category_scores_gemma":[0.01412568,0.000501211,0.002049186,0.003810139,0.0005727712,0.001486844,0.0006816653,0.001765496,0.0108428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004424185,"about_ca_system_score_gemma":0.001438374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009903715,"about_ca_topic_score_gemma":0.01090838,"domain_scores_codex":[0.9978003,0.0005772698,0.0001437012,0.0009847606,0.0002534894,0.0002404548],"domain_scores_gemma":[0.9840487,0.01161938,0.001631507,0.0008496351,0.001433887,0.0004169202],"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":[0.004033486,0.0003393407,0.2256149,0.007197777,0.003825353,0.001999469,0.0006133366,0.005922865,0.00335765,0.009198304,0.6317952,0.1061023],"study_design_scores_gemma":[0.002499278,0.00089982,0.3998845,0.006883738,0.003911523,0.005824328,0.002151141,0.02630298,0.001484564,0.03159624,0.5181936,0.000368246],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.07245469,0.009982559,0.05325181,0.002495697,0.002510662,0.000766745,0.8326619,0.01025488,0.01562112],"genre_scores_gemma":[0.5399247,0.007008824,0.06779399,0.00274578,0.001260301,0.003442954,0.3543155,0.004053304,0.01945458],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1078273,"threshold_uncertainty_score":0.3607182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1551511377579242,"score_gpt":0.3612741843355373,"score_spread":0.2061230465776132,"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."}}