{"id":"W4398862962","doi":"10.7910/dvn/qlq0hb","title":"Mapping coronavirus litterature","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Global Security and Public Health","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Nautical Research Society","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Coronavirus; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Virology; Computer science; Medicine; Outbreak; Internal medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007386125,0.000266556,0.0003787049,0.00009406756,0.0006782221,0.0004125806,0.001202553,0.0006657758,0.03540525],"category_scores_gemma":[0.0008135646,0.000286871,0.0001221766,0.0005060273,0.0002235664,0.000407565,0.0003412531,0.0009858481,0.2371299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002331501,"about_ca_system_score_gemma":0.001110027,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0202567,"about_ca_topic_score_gemma":0.007127962,"domain_scores_codex":[0.9972765,0.0004804403,0.0003146423,0.0005270628,0.0007463529,0.0006550183],"domain_scores_gemma":[0.9983026,0.00010861,0.000198648,0.0006494883,0.00008818409,0.0006524389],"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":[0.00001160705,0.00003584998,0.000002774687,0.0001127326,0.00002818725,0.0001380958,0.001555045,1.207979e-7,3.145431e-7,0.001280988,0.9961698,0.0006644786],"study_design_scores_gemma":[0.0001652039,0.00002109039,0.00001750571,0.0000809514,0.00002084051,0.000002587011,0.001254065,8.298924e-7,1.1912e-7,0.0001161554,0.9980215,0.0002991316],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000003530039,0.000005684548,0.000006515548,0.0006052883,0.00162773,0.0003511877,0.9919605,0.0001114365,0.005328134],"genre_scores_gemma":[0.00001064486,0.001936139,0.0000907932,0.00968217,0.001927764,0.00001228977,0.985975,0.00001127464,0.000353895],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2017246,"threshold_uncertainty_score":0.9999583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04509008382249736,"score_gpt":0.3181160930834341,"score_spread":0.2730260092609367,"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."}}