{"id":"W2950598959","doi":"10.1186/s12881-019-0841-8","title":"Using literature-based discovery to identify candidate genes for the interaction between myocardial infarction and depression","year":2019,"lang":"en","type":"article","venue":"BMC Medical Genetics","topic":"Cardiac Fibrosis and Remodeling","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China; University of Lethbridge","keywords":"Human genetics; Myocardial infarction; Depression (economics); Candidate gene; Genome Biology; Computational biology; Gene; Biology; Genetics; Bioinformatics; Medicine; Genomics; Internal medicine; Genome","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.001592295,0.0006016882,0.0007911669,0.01721083,0.0007132463,0.001413432,0.0007577156,0.0005113683,0.003380501],"category_scores_gemma":[0.006268762,0.0001608179,0.001337258,0.01044612,0.0003147193,0.0007608772,0.0007368434,0.0003915342,0.000916256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007960867,"about_ca_system_score_gemma":0.001906776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002449246,"about_ca_topic_score_gemma":0.004438261,"domain_scores_codex":[0.9990789,0.0001515215,0.0001624178,0.0002371939,0.0002971571,0.00007279975],"domain_scores_gemma":[0.9939872,0.003886926,0.001027756,0.0001468716,0.0007013252,0.0002497859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002199487,0.0005279658,0.5824168,0.01294572,0.002114882,0.01042412,0.002048361,0.003709166,0.04837623,0.003785368,0.01111774,0.3203342],"study_design_scores_gemma":[0.000282562,0.001065435,0.8599194,0.002069435,0.005525603,0.01373578,0.002699642,0.03938391,0.01782467,0.008526734,0.04876776,0.0001990119],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8911596,0.02458385,0.03426192,0.001491898,0.0001596706,0.001154718,0.03799467,0.00111941,0.008074322],"genre_scores_gemma":[0.8588599,0.006449811,0.0959843,0.0003351025,0.0002017971,0.0007204001,0.03594195,0.00007015212,0.001436544],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01721083,"threshold_uncertainty_score":0.01130891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04034019194613736,"score_gpt":0.359535764564601,"score_spread":0.3191955726184637,"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."}}