{"id":"W4205893596","doi":"10.32384/jeahil17465","title":"Building a Systematic Online Living Evidence Summary of COVID-19 Research","year":2021,"lang":"en","type":"article","venue":"Journal of EAHIL","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Medical Research Council","keywords":"Coronavirus disease 2019 (COVID-19); Pace; Relevance (law); Workflow; Pandemic; 2019-20 coronavirus outbreak; Data science; Crowdsourcing; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Quality (philosophy); Computer science; World Wide Web; Political science; Medicine; Geography","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2423297,0.002961028,0.006317564,0.0731183,0.005226161,0.0167318,0.006909821,0.005740854,0.01800005],"category_scores_gemma":[0.5001454,0.003608878,0.008186883,0.02710027,0.00248673,0.01881858,0.01821917,0.007136894,0.005463595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009472859,"about_ca_system_score_gemma":0.06977899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007443316,"about_ca_topic_score_gemma":0.02491669,"domain_scores_codex":[0.7472867,0.09368318,0.1181344,0.01181725,0.0269831,0.002095299],"domain_scores_gemma":[0.3729493,0.3655182,0.08270875,0.04404747,0.124429,0.01034733],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0007298712,0.0002792158,0.008707572,0.297312,0.005261927,0.001176517,0.01860385,0.003375112,0.004514524,0.01535561,0.1452253,0.4994586],"study_design_scores_gemma":[0.0006283245,0.0005915512,0.008377708,0.3540005,0.007989225,0.0004008054,0.007291303,0.003349345,0.003291604,0.03158774,0.5819363,0.0005556537],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03209739,0.1530986,0.3388831,0.1388382,0.0142441,0.1321954,0.1405096,0.01060712,0.0395266],"genre_scores_gemma":[0.04688542,0.03913843,0.8064873,0.01070762,0.001798787,0.05966224,0.03054738,0.0009654904,0.003807433],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7576703,"threshold_uncertainty_score":0.9343423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2321527880595403,"score_gpt":0.4891142412848818,"score_spread":0.2569614532253415,"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."}}