{"id":"W3094057148","doi":"10.5260/chara.22.2.43","title":"ProQuest Coronavirus Research Database","year":2020,"lang":"en","type":"article","venue":"The Charleston Advisor","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Coronavirus; Pandemic; Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Medicine; Disease; Infectious disease (medical specialty)","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":[],"consensus_categories":[],"category_scores_codex":[0.004083938,0.0008048122,0.001566585,0.005960317,0.001007023,0.004280033,0.002659207,0.001889606,0.1701915],"category_scores_gemma":[0.02198279,0.0005243362,0.0009755553,0.005801358,0.0003094595,0.003078917,0.00210561,0.002019808,0.1059275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001055625,"about_ca_system_score_gemma":0.003246519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002450574,"about_ca_topic_score_gemma":0.003124289,"domain_scores_codex":[0.9974497,0.0005857759,0.0005682042,0.0004506393,0.0007743688,0.0001712861],"domain_scores_gemma":[0.9839388,0.005623022,0.001600766,0.002041233,0.004947521,0.001848791],"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":[0.0004227203,0.00006791362,0.001614338,0.0009360695,0.00004304642,0.0001000645,0.00005962263,0.0001967171,0.0003800551,0.001899079,0.9742402,0.02004015],"study_design_scores_gemma":[0.0002377432,0.00006342967,0.00282992,0.0003243258,0.00004885383,0.0002927171,0.00006315979,0.0006577363,0.0005669369,0.00392314,0.9909508,0.00004113866],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"commentary","genre_scores_codex":[0.002808107,0.002491911,0.003018536,0.003534956,0.0004412839,0.0006845195,0.9323714,0.006071351,0.04857796],"genre_scores_gemma":[0.006762321,0.001420863,0.007527543,0.002027714,0.0003509005,0.0009755617,0.969058,0.001219323,0.01065777],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.1701915,"threshold_uncertainty_score":0.5693473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6790202496771239,"score_gpt":0.6015163348701325,"score_spread":0.07750391480699148,"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."}}